Advances in Neural Information Processing Systems 35

NeurIPS 2022

Edited by S. Koyejo and S. Mohamed and A. Agarwal and D. Belgrave and K. Cho and A. Oh

ISBN: 9781713871088

2834 papers

Federated Submodel Optimization for Hot and Cold Data Features Yucheng Ding, Chaoyue Niu, Fan Wu, Shaojie Tang, Chengfei Lyu, yanghe feng, Guihai Chen
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On Kernelized Multi-Armed Bandits with Constraints Xingyu Zhou, Bo Ji
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Geometric Order Learning for Rank Estimation Seon-Ho Lee, Nyeong Ho Shin, Chang-Su Kim
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Structured Recognition for Generative Models with Explaining Away Changmin Yu, Hugo Soulat, Neil Burgess, Maneesh Sahani
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NAS-Bench-Graph: Benchmarking Graph Neural Architecture Search Yijian Qin, Ziwei Zhang, Xin Wang, Zeyang Zhang, Wenwu Zhu
Datasets and Benchmarks Track
Fast Bayesian Coresets via Subsampling and Quasi-Newton Refinement Cian Naik, Judith Rousseau, Trevor Campbell
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What You See is What You Classify: Black Box Attributions Steven Stalder, Nathanael Perraudin, Radhakrishna Achanta, Fernando Perez-Cruz, Michele Volpi
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Adaptive Interest for Emphatic Reinforcement Learning Martin Klissarov, Rasool Fakoor, Jonas W Mueller, Kavosh Asadi, Taesup Kim, Alexander J Smola
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Scaling & Shifting Your Features: A New Baseline for Efficient Model Tuning Dongze Lian, Daquan Zhou, Jiashi Feng, Xinchao Wang
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Zero-Shot Video Question Answering via Frozen Bidirectional Language Models Antoine Yang, Antoine Miech, Josef Sivic, Ivan Laptev, Cordelia Schmid
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Active Learning with Neural Networks: Insights from Nonparametric Statistics Yinglun Zhu, Robert Nowak
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IM-Loss: Information Maximization Loss for Spiking Neural Networks Yufei Guo, Yuanpei Chen, Liwen Zhang, Xiaode Liu, Yinglei Wang, Xuhui Huang, Zhe Ma
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Using natural language and program abstractions to instill human inductive biases in machines Sreejan Kumar, Carlos G. Correa, Ishita Dasgupta, Raja Marjieh, Michael Y Hu, Robert Hawkins, Jonathan D Cohen, nathaniel daw, Karthik Narasimhan, Tom Griffiths
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Second Thoughts are Best: Learning to Re-Align With Human Values from Text Edits Ruibo Liu, Chenyan Jia, Ge Zhang, Ziyu Zhuang, Tony Liu, Soroush Vosoughi
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SatMAE: Pre-training Transformers for Temporal and Multi-Spectral Satellite Imagery Yezhen Cong, Samar Khanna, Chenlin Meng, Patrick Liu, Erik Rozi, Yutong He, Marshall Burke, David Lobell, Stefano Ermon
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On Sample Optimality in Personalized Collaborative and Federated Learning Mathieu Even, Laurent Massoulié, Kevin Scaman
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Offline Multi-Agent Reinforcement Learning with Knowledge Distillation Wei-Cheng Tseng, Tsun-Hsuan Johnson Wang, Yen-Chen Lin, Phillip Isola
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Decentralized Gossip-Based Stochastic Bilevel Optimization over Communication Networks Shuoguang Yang, Xuezhou Zhang, Mengdi Wang
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Conditional Meta-Learning of Linear Representations Giulia Denevi, Massimiliano Pontil, Carlo Ciliberto
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Theory and Approximate Solvers for Branched Optimal Transport with Multiple Sources Peter Lippmann, Enrique Fita Sanmartín, Fred A. Hamprecht
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CHIMLE: Conditional Hierarchical IMLE for Multimodal Conditional Image Synthesis Shichong Peng, Seyed Alireza Moazenipourasil, Ke Li
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Active Ranking without Strong Stochastic Transitivity Hao Lou, Tao Jin, Yue Wu, Pan Xu, Quanquan Gu, Farzad Farnoud
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Offline Goal-Conditioned Reinforcement Learning via $f$-Advantage Regression Jason Yecheng Ma, Jason Yan, Dinesh Jayaraman, Osbert Bastani
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Rethinking and Improving Robustness of Convolutional Neural Networks: a Shapley Value-based Approach in Frequency Domain Yiting Chen, Qibing Ren, Junchi Yan
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Adversarial Style Augmentation for Domain Generalized Urban-Scene Segmentation Zhun Zhong, Yuyang Zhao, Gim Hee Lee, Nicu Sebe
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Fully Sparse 3D Object Detection Lue Fan, Feng Wang, Naiyan Wang, ZHAO-XIANG ZHANG
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Diffusion Visual Counterfactual Explanations Maximilian Augustin, Valentyn Boreiko, Francesco Croce, Matthias Hein
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Recurrent Video Restoration Transformer with Guided Deformable Attention Jingyun Liang, Yuchen Fan, Xiaoyu Xiang, Rakesh Ranjan, Eddy Ilg, Simon Green, Jiezhang Cao, Kai Zhang, Radu Timofte, Luc V Gool
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A Consolidated Cross-Validation Algorithm for Support Vector Machines via Data Reduction Boxiang Wang, Archer Yang
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On-Demand Sampling: Learning Optimally from Multiple Distributions Nika Haghtalab, Michael I. Jordan, Eric Zhao
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Asynchronous SGD Beats Minibatch SGD Under Arbitrary Delays Konstantin Mishchenko, Francis R. Bach, Mathieu Even, Blake E Woodworth
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Coresets for Relational Data and The Applications Jiaxiang Chen, Qingyuan Yang, Ruomin Huang, Hu Ding
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Model-Based Offline Reinforcement Learning with Pessimism-Modulated Dynamics Belief Kaiyang Guo, Shao Yunfeng, Yanhui Geng
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Generating Training Data with Language Models: Towards Zero-Shot Language Understanding Yu Meng, Jiaxin Huang, Yu Zhang, Jiawei Han
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Wavelet Score-Based Generative Modeling Florentin Guth, Simon Coste, Valentin De Bortoli, Stephane Mallat
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Robust Binary Models by Pruning Randomly-initialized Networks Chen Liu, Ziqi Zhao, Sabine Süsstrunk, Mathieu Salzmann
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Why do tree-based models still outperform deep learning on typical tabular data? Leo Grinsztajn, Edouard Oyallon, Gael Varoquaux
Datasets and Benchmarks Track
Generalizing Consistent Multi-Class Classification with Rejection to be Compatible with Arbitrary Losses Yuzhou Cao, Tianchi Cai, Lei Feng, Lihong Gu, Jinjie GU, Bo An, Gang Niu, Masashi Sugiyama
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Markovian Interference in Experiments Vivek Farias, Andrew Li, Tianyi Peng, Andrew Zheng
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Identifiability and generalizability from multiple experts in Inverse Reinforcement Learning Paul Rolland, Luca Viano, Norman Schürhoff, Boris Nikolov, Volkan Cevher
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Parallel Tempering With a Variational Reference Nikola Surjanovic, Saifuddin Syed, Alexandre Bouchard-Côté, Trevor Campbell
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Provably Efficient Reinforcement Learning in Partially Observable Dynamical Systems Masatoshi Uehara, Ayush Sekhari, Jason Lee, Nathan Kallus, Wen Sun
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Off-Policy Evaluation for Episodic Partially Observable Markov Decision Processes under Non-Parametric Models Rui Miao, Zhengling Qi, Xiaoke Zhang
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Efficient Knowledge Distillation from Model Checkpoints Chaofei Wang, Qisen Yang, Rui Huang, Shiji Song, Gao Huang
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Decoupled Self-supervised Learning for Graphs Teng Xiao, Zhengyu Chen, Zhimeng Guo, Zeyang Zhuang, Suhang Wang
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Shadow Knowledge Distillation: Bridging Offline and Online Knowledge Transfer Lujun Li, ZHE JIN
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ComENet: Towards Complete and Efficient Message Passing for 3D Molecular Graphs Limei Wang, Yi Liu, Yuchao Lin, Haoran Liu, Shuiwang Ji
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VLMbench: A Compositional Benchmark for Vision-and-Language Manipulation Kaizhi Zheng, Xiaotong Chen, Odest Chadwicke Jenkins, Xin Wang
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Tiered Reinforcement Learning: Pessimism in the Face of Uncertainty and Constant Regret Jiawei Huang, Li Zhao, Tao Qin, Wei Chen, Nan Jiang, Tie-Yan Liu
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Between Stochastic and Adversarial Online Convex Optimization: Improved Regret Bounds via Smoothness Sarah Sachs, Hedi Hadiji, Tim van Erven, Cristóbal Guzmán
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Differentially Private Learning Needs Hidden State (Or Much Faster Convergence) Jiayuan Ye, Reza Shokri
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BR-SNIS: Bias Reduced Self-Normalized Importance Sampling Gabriel Cardoso, Sergey Samsonov, Achille Thin, Eric Moulines, Jimmy Olsson
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Learning to Configure Computer Networks with Neural Algorithmic Reasoning Luca Beurer-Kellner, Martin Vechev, Laurent Vanbever, Petar Veličković
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Early Stage Convergence and Global Convergence of Training Mildly Parameterized Neural Networks Mingze Wang, Chao Ma
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On Divergence Measures for Bayesian Pseudocoresets Balhae Kim, Jungwon Choi, Seanie Lee, Yoonho Lee, Jung-Woo Ha, Juho Lee
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Unsupervised Learning of Equivariant Structure from Sequences Takeru Miyato, Masanori Koyama, Kenji Fukumizu
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Multi-Class $H$-Consistency Bounds Pranjal Awasthi, Anqi Mao, Mehryar Mohri, Yutao Zhong
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On the Frequency-bias of Coordinate-MLPs Sameera Ramasinghe, Lachlan E. MacDonald, Simon Lucey
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DC-BENCH: Dataset Condensation Benchmark Justin CUI, Ruochen Wang, Si Si, Cho-Jui Hsieh
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Mask Matching Transformer for Few-Shot Segmentation siyu jiao, Gengwei Zhang, Shant Navasardyan, Ling Chen, Yao Zhao, Yunchao Wei, Humphrey Shi
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Queue Up Your Regrets: Achieving the Dynamic Capacity Region of Multiplayer Bandits Ilai Bistritz, Nicholas Bambos
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Differentially Private Covariance Revisited Wei Dong, Yuting Liang, Ke Yi
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Trimmed Maximum Likelihood Estimation for Robust Generalized Linear Model Pranjal Awasthi, Abhimanyu Das, Weihao Kong, Rajat Sen
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Causal Discovery in Linear Latent Variable Models Subject to Measurement Error Yuqin Yang, AmirEmad Ghassami, Mohamed Nafea, Negar Kiyavash, Kun Zhang, Ilya Shpitser
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Density-driven Regularization for Out-of-distribution Detection Wenjian Huang, Hao Wang, Jiahao Xia, Chengyan Wang, Jianguo Zhang
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Sparsity in Continuous-Depth Neural Networks Hananeh Aliee, Till Richter, Mikhail Solonin, Ignacio Ibarra, Fabian J. Theis, Niki Kilbertus
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Environment Diversification with Multi-head Neural Network for Invariant Learning Bo-Wei Huang, Keng-Te Liao, Chang-Sheng Kao, Shou-De Lin
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Learning Probabilistic Models from Generator Latent Spaces with Hat EBM Mitch Hill, Erik Nijkamp, Jonathan Mitchell, Bo Pang, Song-Chun Zhu
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Learning Best Combination for Efficient N:M Sparsity Yuxin Zhang, Mingbao Lin, ZhiHang Lin, Yiting Luo, Ke Li, Fei Chao, Yongjian Wu, Rongrong Ji
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Why Do Artificially Generated Data Help Adversarial Robustness Yue Xing, Qifan Song, Guang Cheng
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Neural Surface Reconstruction of Dynamic Scenes with Monocular RGB-D Camera Hongrui Cai, Wanquan Feng, Xuetao Feng, Yan Wang, Juyong Zhang
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Global Optimal K-Medoids Clustering of One Million Samples Jiayang Ren, Kaixun Hua, Yankai Cao
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Batch Multi-Fidelity Active Learning with Budget Constraints Shibo Li, Jeff M Phillips, Xin Yu, Robert Kirby, Shandian Zhe
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UniCLIP: Unified Framework for Contrastive Language-Image Pre-training Janghyeon Lee, Jongsuk Kim, Hyounguk Shon, Bumsoo Kim, Seung Hwan Kim, Honglak Lee, Junmo Kim
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Efficient Multi-agent Communication via Self-supervised Information Aggregation Cong Guan, Feng Chen, Lei Yuan, Chenghe Wang, Hao Yin, Zongzhang Zhang, Yang Yu
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Accelerated Training of Physics-Informed Neural Networks (PINNs) using Meshless Discretizations Ramansh Sharma, Varun Shankar
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DOPE: Doubly Optimistic and Pessimistic Exploration for Safe Reinforcement Learning Archana Bura, Aria HasanzadeZonuzy, Dileep Kalathil, Srinivas Shakkottai, Jean-Francois Chamberland
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Improved Regret Analysis for Variance-Adaptive Linear Bandits and Horizon-Free Linear Mixture MDPs Yeoneung Kim, Insoon Yang, Kwang-Sung Jun
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Communication-Efficient Topologies for Decentralized Learning with $O(1)$ Consensus Rate Zhuoqing Song, Weijian Li, Kexin Jin, Lei Shi, Ming Yan, Wotao Yin, Kun Yuan
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Moderate-fitting as a Natural Backdoor Defender for Pre-trained Language Models Biru Zhu, Yujia Qin, Ganqu Cui, Yangyi Chen, Weilin Zhao, Chong Fu, Yangdong Deng, Zhiyuan Liu, Jingang Wang, Wei Wu, Maosong Sun, Ming Gu
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Dataset Distillation via Factorization Songhua Liu, Kai Wang, Xingyi Yang, Jingwen Ye, Xinchao Wang
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Adaptive Sampling for Discovery Ziping Xu, Eunjae Shim, Ambuj Tewari, Paul Zimmerman
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A Large Scale Search Dataset for Unbiased Learning to Rank Lixin Zou, Haitao Mao, Xiaokai Chu, Jiliang Tang, Wenwen Ye, Shuaiqiang Wang, Dawei Yin
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SegNeXt: Rethinking Convolutional Attention Design for Semantic Segmentation Meng-Hao Guo, Cheng-Ze Lu, Qibin Hou, Zhengning Liu, Ming-Ming Cheng, Shi-min Hu
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Understanding Hyperdimensional Computing for Parallel Single-Pass Learning Tao Yu, Yichi Zhang, Zhiru Zhang, Christopher M De Sa
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Syndicated Bandits: A Framework for Auto Tuning Hyper-parameters in Contextual Bandit Algorithms QIN DING, Yue Kang, Yi-Wei Liu, Thomas Chun Man Lee, Cho-Jui Hsieh, James Sharpnack
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Benign, Tempered, or Catastrophic: Toward a Refined Taxonomy of Overfitting Neil Mallinar, James Simon, Amirhesam Abedsoltan, Parthe Pandit, Misha Belkin, Preetum Nakkiran
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Pre-trained Adversarial Perturbations Yuanhao Ban, Yinpeng Dong
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An Empirical Study on Disentanglement of Negative-free Contrastive Learning Jinkun Cao, Ruiqian Nai, Qing Yang, Jialei Huang, Yang Gao
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MABSplit: Faster Forest Training Using Multi-Armed Bandits Mo Tiwari, Ryan Kang, Jaeyong Lee, Chris Piech, Ilan Shomorony, Sebastian Thrun, Martin J Zhang
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Counterfactual Fairness with Partially Known Causal Graph Aoqi Zuo, Susan Wei, Tongliang Liu, Bo Han, Kun Zhang, Mingming Gong
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Controlled Sparsity via Constrained Optimization or: How I Learned to Stop Tuning Penalties and Love Constraints Jose Gallego-Posada, Juan Ramirez, Akram Erraqabi, Yoshua Bengio, Simon Lacoste-Julien
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Algorithms and Hardness for Learning Linear Thresholds from Label Proportions Rishi Saket
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Predictive Coding beyond Gaussian Distributions Luca Pinchetti, Tommaso Salvatori, Yordan Yordanov, Beren Millidge, Yuhang Song, Thomas Lukasiewicz
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Semi-supervised Active Linear Regression Nived Rajaraman, Fnu Devvrit, Pranjal Awasthi
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Boosting Barely Robust Learners: A New Perspective on Adversarial Robustness Avrim Blum, Omar Montasser, Greg Shakhnarovich, Hongyang Zhang
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Decision-Focused Learning without Decision-Making: Learning Locally Optimized Decision Losses Sanket Shah, Kai Wang, Bryan Wilder, Andrew Perrault, Milind Tambe
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Neural Stochastic PDEs: Resolution-Invariant Learning of Continuous Spatiotemporal Dynamics Cristopher Salvi, Maud Lemercier, Andris Gerasimovics
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Okapi: Generalising Better by Making Statistical Matches Match Myles Bartlett, Sara Romiti, Viktoriia Sharmanska, Novi Quadrianto
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Revisiting Heterophily For Graph Neural Networks Sitao Luan, Chenqing Hua, Qincheng Lu, Jiaqi Zhu, Mingde Zhao, Shuyuan Zhang, Xiao-Wen Chang, Doina Precup
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Museformer: Transformer with Fine- and Coarse-Grained Attention for Music Generation Botao Yu, Peiling Lu, Rui Wang, Wei Hu, Xu Tan, Wei Ye, Shikun Zhang, Tao Qin, Tie-Yan Liu
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Emergent Communication: Generalization and Overfitting in Lewis Games Mathieu Rita, Corentin Tallec, Paul Michel, Jean-Bastien Grill, Olivier Pietquin, Emmanuel Dupoux, Florian Strub
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Towards Efficient Post-training Quantization of Pre-trained Language Models Haoli Bai, Lu Hou, Lifeng Shang, Xin Jiang, Irwin King, Michael R Lyu
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TweetNERD - End to End Entity Linking Benchmark for Tweets Shubhanshu Mishra, Aman Saini, Raheleh Makki, Sneha Mehta, Aria Haghighi, Ali Mollahosseini
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Riemannian Neural SDE: Learning Stochastic Representations on Manifolds Sung Woo Park, Hyomin Kim, Kyungjae Lee, Junseok Kwon
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OccGen: Selection of Real-world Multilingual Parallel Data Balanced in Gender within Occupations Marta Costa-jussà, Christine Basta, Oriol Domingo, André Rubungo
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Learning in Observable POMDPs, without Computationally Intractable Oracles Noah Golowich, Ankur Moitra, Dhruv Rohatgi
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Cross-Image Context for Single Image Inpainting Tingliang Feng, Wei Feng, Weiqi Li, Di Lin
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Efficient and Effective Augmentation Strategy for Adversarial Training Sravanti Addepalli, Samyak Jain, Venkatesh Babu R
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Multi-Sample Training for Neural Image Compression Tongda Xu, Yan Wang, Dailan He, Chenjian Gao, Han Gao, Kunzan Liu, Hongwei Qin
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Adaptive Data Debiasing through Bounded Exploration Yifan Yang, Yang Liu, Parinaz Naghizadeh
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Learning to Navigate Wikipedia by Taking Random Walks Manzil Zaheer, Kenneth Marino, Will Grathwohl, John Schultz, Wendy Shang, Sheila Babayan, Arun Ahuja, Ishita Dasgupta, Christine Kaeser-Chen, Rob Fergus
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When does return-conditioned supervised learning work for offline reinforcement learning? David Brandfonbrener, Alberto Bietti, Jacob Buckman, Romain Laroche, Joan Bruna
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Provable Subspace Identification Under Post-Nonlinear Mixtures Qi Lyu, Xiao Fu
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S$^3$-NeRF: Neural Reflectance Field from Shading and Shadow under a Single Viewpoint Wenqi Yang, Guanying Chen, Chaofeng Chen, Zhenfang Chen, Kwan-Yee K. Wong
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AdaFocal: Calibration-aware Adaptive Focal Loss Arindam Ghosh, Thomas Schaaf, Matthew Gormley
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PDEBench: An Extensive Benchmark for Scientific Machine Learning Makoto Takamoto, Timothy Praditia, Raphael Leiteritz, Daniel MacKinlay, Francesco Alesiani, Dirk Pflüger, Mathias Niepert
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Learning Robust Dynamics through Variational Sparse Gating Arnav Kumar Jain, Shivakanth Sujit, Shruti Joshi, Vincent Michalski, Danijar Hafner, Samira Ebrahimi Kahou
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Where to Pay Attention in Sparse Training for Feature Selection? Ghada Sokar, Zahra Atashgahi, Mykola Pechenizkiy, Decebal Constantin Mocanu
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Maximizing Revenue under Market Shrinkage and Market Uncertainty Maria-Florina F Balcan, Siddharth Prasad, Tuomas Sandholm
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General Cutting Planes for Bound-Propagation-Based Neural Network Verification Huan Zhang, Shiqi Wang, Kaidi Xu, Linyi Li, Bo Li, Suman Jana, Cho-Jui Hsieh, J. Zico Kolter
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StrokeRehab: A Benchmark Dataset for Sub-second Action Identification Aakash Kaku, Kangning Liu, Avinash Parnandi, Haresh Rengaraj Rajamohan, Kannan Venkataramanan, Anita Venkatesan, Audre Wirtanen, Natasha Pandit, Heidi Schambra, Carlos Fernandez-Granda
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An $\alpha$-regret analysis of Adversarial Bilateral Trade Yossi Azar, Amos Fiat, Federico Fusco
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LDSA: Learning Dynamic Subtask Assignment in Cooperative Multi-Agent Reinforcement Learning Mingyu Yang, Jian Zhao, Xunhan Hu, Wengang Zhou, Jiangcheng Zhu, Houqiang Li
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Mildly Conservative Q-Learning for Offline Reinforcement Learning Jiafei Lyu, Xiaoteng Ma, Xiu Li, Zongqing Lu
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Iterative Feature Matching: Toward Provable Domain Generalization with Logarithmic Environments Yining Chen, Elan Rosenfeld, Mark Sellke, Tengyu Ma, Andrej Risteski
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Certifying Robust Graph Classification under Orthogonal Gromov-Wasserstein Threats Hongwei Jin, Zishun Yu, Xinhua Zhang
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Functional Ensemble Distillation Coby Penso, Idan Achituve, Ethan Fetaya
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Use-Case-Grounded Simulations for Explanation Evaluation Valerie Chen, Nari Johnson, Nicholay Topin, Gregory Plumb, Ameet Talwalkar
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Lethal Dose Conjecture on Data Poisoning Wenxiao Wang, Alexander Levine, Soheil Feizi
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Online Decision Mediation Daniel Jarrett, Alihan Hüyük, Mihaela van der Schaar
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Neural-Symbolic Entangled Framework for Complex Query Answering Zezhong Xu, Wen Zhang, Peng Ye, Hui Chen, Huajun Chen
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Reinforcement Learning with Automated Auxiliary Loss Search Tairan He, Yuge Zhang, Kan Ren, Minghuan Liu, Che Wang, Weinan Zhang, Yuqing Yang, Dongsheng Li
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FinRL-Meta: Market Environments and Benchmarks for Data-Driven Financial Reinforcement Learning Xiao-Yang Liu, Ziyi Xia, Jingyang Rui, Jiechao Gao, Hongyang Yang, Ming Zhu, Christina Wang, Zhaoran Wang, Jian Guo
Datasets and Benchmarks Track
TempEL: Linking Dynamically Evolving and Newly Emerging Entities Klim Zaporojets, Lucie-Aimée Kaffee, Johannes Deleu, Thomas Demeester, Chris Develder, Isabelle Augenstein
Datasets and Benchmarks Track
M$^4$I: Multi-modal Models Membership Inference Pingyi Hu, Zihan Wang, Ruoxi Sun, Hu Wang, Minhui Xue
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Best of Both Worlds Model Selection Aldo Pacchiano, Christoph Dann, Claudio Gentile
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The Unreasonable Effectiveness of Fully-Connected Layers for Low-Data Regimes Peter Kocsis, Peter Súkeník, Guillem Braso, Matthias Niessner, Laura Leal-Taixé, Ismail Elezi
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Augmentations in Hypergraph Contrastive Learning: Fabricated and Generative Tianxin Wei, Yuning You, Tianlong Chen, Yang Shen, Jingrui He, Zhangyang Wang
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On the Global Convergence Rates of Decentralized Softmax Gradient Play in Markov Potential Games Runyu Zhang, Jincheng Mei, Bo Dai, Dale Schuurmans, Na Li
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Sym-NCO: Leveraging Symmetricity for Neural Combinatorial Optimization Minsu Kim, Junyoung Park, Jinkyoo Park
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Few-Shot Parameter-Efficient Fine-Tuning is Better and Cheaper than In-Context Learning Haokun Liu, Derek Tam, Mohammed Muqeeth, Jay Mohta, Tenghao Huang, Mohit Bansal, Colin A Raffel
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HF-NeuS: Improved Surface Reconstruction Using High-Frequency Details Yiqun Wang, Ivan Skorokhodov, Peter Wonka
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On the Epistemic Limits of Personalized Prediction Lucas Monteiro Paes, Carol Long, Berk Ustun, Flavio Calmon
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DeepInteraction: 3D Object Detection via Modality Interaction Zeyu Yang, Jiaqi Chen, Zhenwei Miao, Wei Li, Xiatian Zhu, Li Zhang
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Deep Differentiable Logic Gate Networks Felix Petersen, Christian Borgelt, Hilde Kuehne, Oliver Deussen
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Maximizing and Satisficing in Multi-armed Bandits with Graph Information Parth Thaker, Mohit Malu, Nikhil Rao, Gautam Dasarathy
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MoGDE: Boosting Mobile Monocular 3D Object Detection with Ground Depth Estimation Yunsong Zhou, Quan Liu, Hongzi Zhu, Yunzhe Li, Shan Chang, Minyi Guo
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Causality Preserving Chaotic Transformation and Classification using Neurochaos Learning Harikrishnan N B, Aditi Kathpalia, Nithin Nagaraj
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GOOD: A Graph Out-of-Distribution Benchmark Shurui Gui, Xiner Li, Limei Wang, Shuiwang Ji
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CascadeXML: Rethinking Transformers for End-to-end Multi-resolution Training in Extreme Multi-label Classification Siddhant Kharbanda, Atmadeep Banerjee, Erik Schultheis, Rohit Babbar
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VF-PS: How to Select Important Participants in Vertical Federated Learning, Efficiently and Securely? Jiawei Jiang, Lukas Burkhalter, Fangcheng Fu, Bolin Ding, Bo Du, Anwar Hithnawi, Bo Li, Ce Zhang
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PopArt: Efficient Sparse Regression and Experimental Design for Optimal Sparse Linear Bandits Kyoungseok Jang, Chicheng Zhang, Kwang-Sung Jun
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Augmenting Online Algorithms with $\varepsilon$-Accurate Predictions Anupam Gupta, Debmalya Panigrahi, Bernardo Subercaseaux, Kevin Sun
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Unsupervised Multi-Object Segmentation by Predicting Probable Motion Patterns Laurynas Karazija, Subhabrata Choudhury, Iro Laina, Christian Rupprecht, Andrea Vedaldi
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Incrementality Bidding via Reinforcement Learning under Mixed and Delayed Rewards Ashwinkumar Badanidiyuru Varadaraja, Zhe Feng, Tianxi Li, Haifeng Xu
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Masked Generative Adversarial Networks are Data-Efficient Generation Learners Jiaxing Huang, Kaiwen Cui, Dayan Guan, Aoran Xiao, Fangneng Zhan, Shijian Lu, Shengcai Liao, Eric P. Xing
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What You See is What You Get: Principled Deep Learning via Distributional Generalization Bogdan Kulynych, Yao-Yuan Yang, Yaodong Yu, Jarosław Błasiok, Preetum Nakkiran
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Towards Understanding the Condensation of Neural Networks at Initial Training Hanxu Zhou, Zhou Qixuan, Tao Luo, Yaoyu Zhang, Zhi-Qin Xu
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CoNT: Contrastive Neural Text Generation Chenxin An, Jiangtao Feng, Kai Lv, Lingpeng Kong, Xipeng Qiu, Xuanjing Huang
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GAPX: Generalized Autoregressive Paraphrase-Identification X Yifei Zhou, Renyu Li, Hayden Housen, Ser Nam Lim
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Scalable Infomin Learning Yanzhi Chen, weihao sun, Yingzhen Li, Adrian Weller
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Learning to Accelerate Partial Differential Equations via Latent Global Evolution Tailin Wu, Takashi Maruyama, Jure Leskovec
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Monte Carlo Augmented Actor-Critic for Sparse Reward Deep Reinforcement Learning from Suboptimal Demonstrations Albert Wilcox, Ashwin Balakrishna, Jules Dedieu, Wyame Benslimane, Daniel Brown, Ken Goldberg
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Not too little, not too much: a theoretical analysis of graph (over)smoothing Nicolas Keriven
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Kernel similarity matching with Hebbian networks Kyle Luther, Sebastian Seung
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HumanLiker: A Human-like Object Detector to Model the Manual Labeling Process Haoran Wei, Ping Guo, Yangguang Zhu, Chenglong Liu, Peng Wang
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Scalable Representation Learning in Linear Contextual Bandits with Constant Regret Guarantees Andrea Tirinzoni, Matteo Papini, Ahmed Touati, Alessandro Lazaric, Matteo Pirotta
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DevFly: Bio-Inspired Development of Binary Connections for Locality Preserving Sparse Codes Tianqi Wei, Rana Alkhoury Maroun, Qinghai Guo, Barbara Webb
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Why neural networks find simple solutions: The many regularizers of geometric complexity Benoit Dherin, Michael Munn, Mihaela Rosca, David Barrett
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Efficiently Computing Local Lipschitz Constants of Neural Networks via Bound Propagation Zhouxing Shi, Yihan Wang, Huan Zhang, J. Zico Kolter, Cho-Jui Hsieh
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A Causal Analysis of Harm Sander Beckers, Hana Chockler, Joseph Halpern
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Seeing the forest and the tree: Building representations of both individual and collective dynamics with transformers Ran Liu, Mehdi Azabou, Max Dabagia, Jingyun Xiao, Eva Dyer
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Semi-Supervised Learning with Decision Trees: Graph Laplacian Tree Alternating Optimization Arman Zharmagambetov, Miguel A. Carreira-Perpinan
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Riemannian Score-Based Generative Modelling Valentin De Bortoli, Emile Mathieu, Michael Hutchinson, James Thornton, Yee Whye Teh, Arnaud Doucet
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Intra-agent speech permits zero-shot task acquisition Chen Yan, Federico Carnevale, Petko I Georgiev, Adam Santoro, Aurelia Guy, Alistair Muldal, Chia-Chun Hung, Joshua Abramson, Timothy Lillicrap, Gregory Wayne
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Free Probability for predicting the performance of feed-forward fully connected neural networks Reda CHHAIBI, Tariq Daouda, Ezechiel Kahn
Main Conference Track
The Minority Matters: A Diversity-Promoting Collaborative Metric Learning Algorithm Shilong Bao, Qianqian Xu, Zhiyong Yang, Yuan He, Xiaochun Cao, Qingming Huang
Main Conference Track
Open-Ended Reinforcement Learning with Neural Reward Functions Robert Meier, Asier Mujika
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A Reduction to Binary Approach for Debiasing Multiclass Datasets Ibrahim M Alabdulmohsin, Jessica Schrouff, Sanmi Koyejo
Main Conference Track
Obj2Seq: Formatting Objects as Sequences with Class Prompt for Visual Tasks Zhiyang Chen, Yousong Zhu, Zhaowen Li, Fan Yang, Wei Li, Haixin Wang, Chaoyang Zhao, Liwei Wu, Rui Zhao, Jinqiao Wang, Ming Tang
Main Conference Track
Learn to Explain: Multimodal Reasoning via Thought Chains for Science Question Answering Pan Lu, Swaroop Mishra, Tanglin Xia, Liang Qiu, Kai-Wei Chang, Song-Chun Zhu, Oyvind Tafjord, Peter Clark, Ashwin Kalyan
Main Conference Track
Few-Shot Audio-Visual Learning of Environment Acoustics Sagnik Majumder, Changan Chen, Ziad Al-Halah, Kristen Grauman
Main Conference Track
The Phenomenon of Policy Churn Tom Schaul, Andre Barreto, John Quan, Georg Ostrovski
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Molecule Generation by Principal Subgraph Mining and Assembling Xiangzhe Kong, Wenbing Huang, Zhixing Tan, Yang Liu
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Implicit Neural Representations with Levels-of-Experts Zekun Hao, Arun Mallya, Serge Belongie, Ming-Yu Liu
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Planning for Sample Efficient Imitation Learning Zhao-Heng Yin, Weirui Ye, Qifeng Chen, Yang Gao
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Concept Activation Regions: A Generalized Framework For Concept-Based Explanations Jonathan Crabbé, Mihaela van der Schaar
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Towards Safe Reinforcement Learning with a Safety Editor Policy Haonan Yu, Wei Xu, Haichao Zhang
Main Conference Track
Understanding Cross-Domain Few-Shot Learning Based on Domain Similarity and Few-Shot Difficulty Jaehoon Oh, Sungnyun Kim, Namgyu Ho, Jin-Hwa Kim, Hwanjun Song, Se-Young Yun
Main Conference Track
Ambiguous Images With Human Judgments for Robust Visual Event Classification Kate Sanders, Reno Kriz, Anqi Liu, Benjamin Van Durme
Datasets and Benchmarks Track
Sustainable Online Reinforcement Learning for Auto-bidding Zhiyu Mou, Yusen Huo, Rongquan Bai, Mingzhou Xie, Chuan Yu, Jian Xu, Bo Zheng
Main Conference Track
Uni-Perceiver-MoE: Learning Sparse Generalist Models with Conditional MoEs Jinguo Zhu, Xizhou Zhu, Wenhai Wang, Xiaohua Wang, Hongsheng Li, Xiaogang Wang, Jifeng Dai
Main Conference Track
Improved Coresets for Euclidean $k$-Means Vincent Cohen-Addad, Kasper Green Larsen, David Saulpic, Chris Schwiegelshohn, Omar Ali Sheikh-Omar
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Accelerated Linearized Laplace Approximation for Bayesian Deep Learning Zhijie Deng, Feng Zhou, Jun Zhu
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Learning to Reason with Neural Networks: Generalization, Unseen Data and Boolean Measures Emmanuel Abbe, Samy Bengio, Elisabetta Cornacchia, Jon M. Kleinberg, Aryo Lotfi, Maithra Raghu, Chiyuan Zhang
Main Conference Track
Using Partial Monotonicity in Submodular Maximization Loay Mualem, Moran Feldman
Main Conference Track
Enhanced Meta Reinforcement Learning via Demonstrations in Sparse Reward Environments Desik Rengarajan, Sapana Chaudhary, Jaewon Kim, Dileep Kalathil, Srinivas Shakkottai
Main Conference Track
Riemannian Diffusion Models Chin-Wei Huang, Milad Aghajohari, Joey Bose, Prakash Panangaden, Aaron C. Courville
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Training and Inference on Any-Order Autoregressive Models the Right Way Andy Shih, Dorsa Sadigh, Stefano Ermon
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Lazy and Fast Greedy MAP Inference for Determinantal Point Process Shinichi Hemmi, Taihei Oki, Shinsaku Sakaue, Kaito Fujii, Satoru Iwata
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Generalization Bounds for Stochastic Gradient Descent via Localized $\varepsilon$-Covers Sejun Park, Umut Simsekli, Murat A Erdogdu
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Semi-Supervised Semantic Segmentation via Gentle Teaching Assistant Ying Jin, Jiaqi Wang, Dahua Lin
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Anytime-Valid Inference For Multinomial Count Data Michael Lindon, Alan Malek
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What I Cannot Predict, I Do Not Understand: A Human-Centered Evaluation Framework for Explainability Methods Julien Colin, Thomas FEL, Remi Cadene, Thomas Serre
Main Conference Track
S4ND: Modeling Images and Videos as Multidimensional Signals with State Spaces Eric Nguyen, Karan Goel, Albert Gu, Gordon Downs, Preey Shah, Tri Dao, Stephen Baccus, Christopher Ré
Main Conference Track
Understanding Programmatic Weak Supervision via Source-aware Influence Function Jieyu Zhang, Haonan Wang, Cheng-Yu Hsieh, Alexander J Ratner
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Approximation with CNNs in Sobolev Space: with Applications to Classification Guohao Shen, Yuling Jiao, Yuanyuan Lin, Jian Huang
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Sample Complexity of Learning Heuristic Functions for Greedy-Best-First and A* Search Shinsaku Sakaue, Taihei Oki
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TransTab: Learning Transferable Tabular Transformers Across Tables Zifeng Wang, Jimeng Sun
Main Conference Track
Perceptual Attacks of No-Reference Image Quality Models with Human-in-the-Loop Weixia Zhang, Dingquan Li, Xiongkuo Min, Guangtao Zhai, Guodong Guo, Xiaokang Yang, Kede Ma
Main Conference Track
Sketch-GNN: Scalable Graph Neural Networks with Sublinear Training Complexity Mucong Ding, Tahseen Rabbani, Bang An, Evan Wang, Furong Huang
Main Conference Track
Tree Mover's Distance: Bridging Graph Metrics and Stability of Graph Neural Networks Ching-Yao Chuang, Stefanie Jegelka
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DivBO: Diversity-aware CASH for Ensemble Learning Yu Shen, Yupeng Lu, Yang Li, Yaofeng Tu, Wentao Zhang, Bin CUI
Main Conference Track
Revisiting Graph Contrastive Learning from the Perspective of Graph Spectrum Nian Liu, Xiao Wang, Deyu Bo, Chuan Shi, Jian Pei
Main Conference Track
Functional Indirection Neural Estimator for Better Out-of-distribution Generalization Kha Pham, Thai Hung Le, Man Ngo, Truyen Tran
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Combinatorial Bandits with Linear Constraints: Beyond Knapsacks and Fairness Qingsong Liu, Weihang Xu, Siwei Wang, Zhixuan Fang
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Will Bilevel Optimizers Benefit from Loops Kaiyi Ji, Mingrui Liu, Yingbin Liang, Lei Ying
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Combining Explicit and Implicit Regularization for Efficient Learning in Deep Networks Dan Zhao
Main Conference Track
MBW: Multi-view Bootstrapping in the Wild Mosam Dabhi, Chaoyang Wang, Tim Clifford, László Jeni, Ian Fasel, Simon Lucey
Datasets and Benchmarks Track
On A Mallows-type Model For (Ranked) Choices Yifan Feng, Yuxuan Tang
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(De-)Randomized Smoothing for Decision Stump Ensembles Miklós Horváth, Mark Müller, Marc Fischer, Martin Vechev
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Learning to Break the Loop: Analyzing and Mitigating Repetitions for Neural Text Generation Jin Xu, Xiaojiang Liu, Jianhao Yan, Deng Cai, Huayang Li, Jian Li
Main Conference Track
Debiased Machine Learning without Sample-Splitting for Stable Estimators Qizhao Chen, Vasilis Syrgkanis, Morgane Austern
Main Conference Track
Near-Optimal Sample Complexity Bounds for Constrained MDPs Sharan Vaswani, Lin Yang, Csaba Szepesvari
Main Conference Track
Integral Probability Metrics PAC-Bayes Bounds Ron Amit, Baruch Epstein, Shay Moran, Ron Meir
Main Conference Track
Bellman Residual Orthogonalization for Offline Reinforcement Learning Andrea Zanette, Martin J Wainwright
Main Conference Track
Quantum Speedups of Optimizing Approximately Convex Functions with Applications to Logarithmic Regret Stochastic Convex Bandits Tongyang Li, Ruizhe Zhang
Main Conference Track
Learning Neural Acoustic Fields Andrew Luo, Yilun Du, Michael Tarr, Josh Tenenbaum, Antonio Torralba, Chuang Gan
Main Conference Track
A Universal Error Measure for Input Predictions Applied to Online Graph Problems Giulia Bernardini, Alexander Lindermayr, Alberto Marchetti-Spaccamela, Nicole Megow, Leen Stougie, Michelle Sweering
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Online Reinforcement Learning for Mixed Policy Scopes Junzhe Zhang, Elias Bareinboim
Main Conference Track
Self-explaining deep models with logic rule reasoning Seungeon Lee, Xiting Wang, Sungwon Han, Xiaoyuan Yi, Xing Xie, Meeyoung Cha
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XTC: Extreme Compression for Pre-trained Transformers Made Simple and Efficient Xiaoxia Wu, Zhewei Yao, Minjia Zhang, Conglong Li, Yuxiong He
Main Conference Track
Meta-Album: Multi-domain Meta-Dataset for Few-Shot Image Classification Ihsan Ullah, Dustin Carrión-Ojeda, Sergio Escalera, Isabelle Guyon, Mike Huisman, Felix Mohr, Jan N. van Rijn, Haozhe Sun, Joaquin Vanschoren, Phan Anh Vu
Datasets and Benchmarks Track
S3GC: Scalable Self-Supervised Graph Clustering Fnu Devvrit, Aditya Sinha, Inderjit S. Dhillon, Prateek Jain
Main Conference Track
Contrastive Neural Ratio Estimation Benjamin K Miller, Christoph Weniger, Patrick Forré
Main Conference Track
An Information-Theoretic Framework for Deep Learning Hong Jun Jeon, Benjamin Van Roy
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Uncoupled Learning Dynamics with $O(\log T)$ Swap Regret in Multiplayer Games Ioannis Anagnostides, Gabriele Farina, Christian Kroer, Chung-Wei Lee, Haipeng Luo, Tuomas Sandholm
Main Conference Track
Robust Semi-Supervised Learning when Not All Classes have Labels Lan-Zhe Guo, Yi-Ge Zhang, Zhi-Fan Wu, Jie-Jing Shao, Yu-Feng Li
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Private Multiparty Perception for Navigation Hui Lu, Mia Chiquier, Carl Vondrick
Main Conference Track
Improving Task-Specific Generalization in Few-Shot Learning via Adaptive Vicinal Risk Minimization Long-Kai Huang, Ying Wei
Main Conference Track
EgoTaskQA: Understanding Human Tasks in Egocentric Videos Baoxiong Jia, Ting Lei, Song-Chun Zhu, Siyuan Huang
Datasets and Benchmarks Track
C-Mixup: Improving Generalization in Regression Huaxiu Yao, Yiping Wang, Linjun Zhang, James Y Zou, Chelsea Finn
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Generalised Mutual Information for Discriminative Clustering Louis Ohl, Pierre-Alexandre Mattei, Charles Bouveyron, Warith HARCHAOUI, Mickaël Leclercq, Arnaud Droit, Frederic Precioso
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Consistent Interpolating Ensembles via the Manifold-Hilbert Kernel Yutong Wang, Clay Scott
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Geo-Neus: Geometry-Consistent Neural Implicit Surfaces Learning for Multi-view Reconstruction Qiancheng Fu, Qingshan Xu, Yew Soon Ong, Wenbing Tao
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Sublinear Algorithms for Hierarchical Clustering Arpit Agarwal, Sanjeev Khanna, Huan Li, Prathamesh Patil
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Is Sortition Both Representative and Fair? Soroush Ebadian, Gregory Kehne, Evi Micha, Ariel D Procaccia, Nisarg Shah
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Beyond Rewards: a Hierarchical Perspective on Offline Multiagent Behavioral Analysis Shayegan Omidshafiei, Andrei Kapishnikov, Yannick Assogba, Lucas Dixon, Been Kim
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Dynamic pricing and assortment under a contextual MNL demand Noemie Perivier, Vineet Goyal
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DGD^2: A Linearly Convergent Distributed Algorithm For High-dimensional Statistical Recovery Marie Maros, Gesualdo Scutari
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Pseudo-Riemannian Graph Convolutional Networks Bo Xiong, Shichao Zhu, Nico Potyka, Shirui Pan, Chuan Zhou, Steffen Staab
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CroCo: Self-Supervised Pre-training for 3D Vision Tasks by Cross-View Completion Philippe Weinzaepfel, Vincent Leroy, Thomas Lucas, Romain BRÉGIER, Yohann Cabon, Vaibhav ARORA, Leonid Antsfeld, Boris Chidlovskii, Gabriela Csurka, Jerome Revaud
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Sound and Complete Verification of Polynomial Networks Elias Abad Rocamora, Mehmet Fatih Sahin, Fanghui Liu, Grigorios Chrysos, Volkan Cevher
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Better SGD using Second-order Momentum Hoang Tran, Ashok Cutkosky
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Learning Predictions for Algorithms with Predictions Misha Khodak, Maria-Florina F Balcan, Ameet Talwalkar, Sergei Vassilvitskii
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Unsupervised Point Cloud Completion and Segmentation by Generative Adversarial Autoencoding Network Changfeng Ma, Yang Yang, Jie Guo, Fei Pan, Chongjun Wang, Yanwen Guo
Main Conference Track
CalFAT: Calibrated Federated Adversarial Training with Label Skewness Chen Chen, Yuchen Liu, Xingjun Ma, Lingjuan Lyu
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Rethinking Generalization in Few-Shot Classification Markus Hiller, Rongkai Ma, Mehrtash Harandi, Tom Drummond
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Stimulative Training of Residual Networks: A Social Psychology Perspective of Loafing Peng Ye, Shengji Tang, Baopu Li, Tao Chen, Wanli Ouyang
Main Conference Track
EGSDE: Unpaired Image-to-Image Translation via Energy-Guided Stochastic Differential Equations Min Zhao, Fan Bao, Chongxuan LI, Jun Zhu
Main Conference Track
Cryptographic Hardness of Learning Halfspaces with Massart Noise Ilias Diakonikolas, Daniel Kane, Pasin Manurangsi, Lisheng Ren
Main Conference Track
Frank-Wolfe-based Algorithms for Approximating Tyler's M-estimator Lior Danon, Dan Garber
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Reinforcement Learning with Non-Exponential Discounting Matthias Schultheis, Constantin A Rothkopf, Heinz Koeppl
Main Conference Track
Picking on the Same Person: Does Algorithmic Monoculture lead to Outcome Homogenization? Rishi Bommasani, Kathleen A. Creel, Ananya Kumar, Dan Jurafsky, Percy Liang
Main Conference Track
Causal Identification under Markov equivalence: Calculus, Algorithm, and Completeness Amin Jaber, Adele Ribeiro, Jiji Zhang, Elias Bareinboim
Main Conference Track
Unravelling the Performance of Physics-informed Graph Neural Networks for Dynamical Systems Abishek Thangamuthu, Gunjan Kumar, Suresh Bishnoi, Ravinder Bhattoo, N M Anoop Krishnan, Sayan Ranu
Datasets and Benchmarks Track
Dynamic Fair Division with Partial Information Gerdus Benade, Daniel Halpern, Alexandros Psomas
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Generalized Variational Inference in Function Spaces: Gaussian Measures meet Bayesian Deep Learning Veit David Wild, Robert Hu, Dino Sejdinovic
Main Conference Track
Communicating Natural Programs to Humans and Machines Sam Acquaviva, Yewen Pu, Marta Kryven, Theodoros Sechopoulos, Catherine Wong, Gabrielle Ecanow, Maxwell Nye, Michael Tessler, Josh Tenenbaum
Datasets and Benchmarks Track
SCAMPS: Synthetics for Camera Measurement of Physiological Signals Daniel McDuff, Miah Wander, Xin Liu, Brian Hill, Javier Hernandez, Jonathan Lester, Tadas Baltrusaitis
Datasets and Benchmarks Track
A Closer Look at Learned Optimization: Stability, Robustness, and Inductive Biases James Harrison, Luke Metz, Jascha Sohl-Dickstein
Main Conference Track
"Lossless" Compression of Deep Neural Networks: A High-dimensional Neural Tangent Kernel Approach lingyu gu, Yongqi Du, yuan zhang, Di Xie, Shiliang Pu, Robert Qiu, Zhenyu Liao
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Privacy of Noisy Stochastic Gradient Descent: More Iterations without More Privacy Loss Jason Altschuler, Kunal Talwar
Main Conference Track
Theseus: A Library for Differentiable Nonlinear Optimization Luis Pineda, Taosha Fan, Maurizio Monge, Shobha Venkataraman, Paloma Sodhi, Ricky T. Q. Chen, Joseph Ortiz, Daniel DeTone, Austin Wang, Stuart Anderson, Jing Dong, Brandon Amos, Mustafa Mukadam
Main Conference Track
K-Radar: 4D Radar Object Detection for Autonomous Driving in Various Weather Conditions Dong-Hee Paek, SEUNG-HYUN KONG, Kevin Tirta Wijaya
Datasets and Benchmarks Track
Asymmetric Temperature Scaling Makes Larger Networks Teach Well Again Xin-Chun Li, Wen-shu Fan, Shaoming Song, Yinchuan Li, bingshuai Li, Shao Yunfeng, De-Chuan Zhan
Main Conference Track
Solving Quantitative Reasoning Problems with Language Models Aitor Lewkowycz, Anders Andreassen, David Dohan, Ethan Dyer, Henryk Michalewski, Vinay Ramasesh, Ambrose Slone, Cem Anil, Imanol Schlag, Theo Gutman-Solo, Yuhuai Wu, Behnam Neyshabur, Guy Gur-Ari, Vedant Misra
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Structural Knowledge Distillation for Object Detection Philip de Rijk, Lukas Schneider, Marius Cordts, Dariu Gavrila
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Thompson Sampling Efficiently Learns to Control Diffusion Processes Mohamad Kazem Shirani Faradonbeh, Mohamad Sadegh Shirani Faradonbeh, Mohsen Bayati
Main Conference Track
Discrete Compositional Representations as an Abstraction for Goal Conditioned Reinforcement Learning Riashat Islam, Hongyu Zang, Anirudh Goyal, Alex M Lamb, Kenji Kawaguchi, Xin Li, Romain Laroche, Yoshua Bengio, Remi Tachet des Combes
Main Conference Track
Graph Convolution Network based Recommender Systems: Learning Guarantee and Item Mixture Powered Strategy Leyan Deng, Defu Lian, Chenwang Wu, Enhong Chen
Main Conference Track
Local Metric Learning for Off-Policy Evaluation in Contextual Bandits with Continuous Actions Haanvid Lee, Jongmin Lee, Yunseon Choi, Wonseok Jeon, Byung-Jun Lee, Yung-Kyun Noh, Kee-Eung Kim
Main Conference Track
Flare7K: A Phenomenological Nighttime Flare Removal Dataset Yuekun Dai, Chongyi Li, Shangchen Zhou, Ruicheng Feng, Chen Change Loy
Datasets and Benchmarks Track
USB: A Unified Semi-supervised Learning Benchmark for Classification Yidong Wang, Hao Chen, Yue Fan, Wang SUN, Ran Tao, Wenxin Hou, Renjie Wang, Linyi Yang, Zhi Zhou, Lan-Zhe Guo, Heli Qi, Zhen Wu, Yu-Feng Li, Satoshi Nakamura, Wei Ye, Marios Savvides, Bhiksha Raj, Takahiro Shinozaki, Bernt Schiele, Jindong Wang, Xing Xie, Yue Zhang
Datasets and Benchmarks Track
Nocturne: a scalable driving benchmark for bringing multi-agent learning one step closer to the real world Eugene Vinitsky, Nathan Lichtlé, Xiaomeng Yang, Brandon Amos, Jakob Foerster
Datasets and Benchmarks Track
Quasi-Newton Methods for Saddle Point Problems Chengchang Liu, Luo Luo
Main Conference Track
Self-Supervised Contrastive Pre-Training For Time Series via Time-Frequency Consistency Xiang Zhang, Ziyuan Zhao, Theodoros Tsiligkaridis, Marinka Zitnik
Main Conference Track
Uncalibrated Models Can Improve Human-AI Collaboration Kailas Vodrahalli, Tobias Gerstenberg, James Y Zou
Main Conference Track
Learning Dynamical Systems via Koopman Operator Regression in Reproducing Kernel Hilbert Spaces Vladimir Kostic, Pietro Novelli, Andreas Maurer, Carlo Ciliberto, Lorenzo Rosasco, Massimiliano Pontil
Main Conference Track
Self-supervised surround-view depth estimation with volumetric feature fusion Jung-Hee Kim, Junhwa Hur, Tien Phuoc Nguyen, Seong-Gyun Jeong
Main Conference Track
CARLANE: A Lane Detection Benchmark for Unsupervised Domain Adaptation from Simulation to multiple Real-World Domains Bonifaz Stuhr, Johann Haselberger, Julian Gebele
Datasets and Benchmarks Track
On Enforcing Better Conditioned Meta-Learning for Rapid Few-Shot Adaptation Markus Hiller, Mehrtash Harandi, Tom Drummond
Main Conference Track
Oracle-Efficient Online Learning for Smoothed Adversaries Nika Haghtalab, Yanjun Han, Abhishek Shetty, Kunhe Yang
Main Conference Track
A Policy-Guided Imitation Approach for Offline Reinforcement Learning Haoran Xu, Li Jiang, Li Jianxiong, Xianyuan Zhan
Main Conference Track
Sample-Efficient Learning of Correlated Equilibria in Extensive-Form Games Ziang Song, Song Mei, Yu Bai
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VectorAdam for Rotation Equivariant Geometry Optimization Selena Zihan Ling, Nicholas Sharp, Alec Jacobson
Main Conference Track
Matrix Multiplicative Weights Updates in Quantum Zero-Sum Games: Conservation Laws & Recurrence Rahul Jain, Georgios Piliouras, Ryann Sim
Main Conference Track
On the Convergence Theory for Hessian-Free Bilevel Algorithms Daouda Sow, Kaiyi Ji, Yingbin Liang
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Equivariant Networks for Crystal Structures Oumar Kaba, Siamak Ravanbakhsh
Main Conference Track
A General Framework for Auditing Differentially Private Machine Learning Fred Lu, Joseph Munoz, Maya Fuchs, Tyler LeBlond, Elliott Zaresky-Williams, Edward Raff, Francis Ferraro, Brian Testa
Main Conference Track
Generalization Analysis on Learning with a Concurrent Verifier Masaaki Nishino, Kengo Nakamura, Norihito Yasuda
Main Conference Track
Spartan: Differentiable Sparsity via Regularized Transportation Kai Sheng Tai, Taipeng Tian, Ser Nam Lim
Main Conference Track
Focal Modulation Networks Jianwei Yang, Chunyuan Li, Xiyang Dai, Jianfeng Gao
Main Conference Track
HSurf-Net: Normal Estimation for 3D Point Clouds by Learning Hyper Surfaces Qing Li, Yu-Shen Liu, Jin-San Cheng, Cheng Wang, Yi Fang, Zhizhong Han
Main Conference Track
Robust Streaming PCA Daniel Bienstock, Minchan Jeong, Apurv Shukla, Se-Young Yun
Main Conference Track
NeMF: Neural Motion Fields for Kinematic Animation Chengan He, Jun Saito, James Zachary, Holly Rushmeier, Yi Zhou
Main Conference Track
Global Normalization for Streaming Speech Recognition in a Modular Framework Ehsan Variani, Ke Wu, Michael D Riley, David Rybach, Matt Shannon, Cyril Allauzen
Main Conference Track
Resource-Adaptive Federated Learning with All-In-One Neural Composition Yiqun Mei, Pengfei Guo, Mo Zhou, Vishal Patel
Main Conference Track
SoteriaFL: A Unified Framework for Private Federated Learning with Communication Compression Zhize Li, Haoyu Zhao, Boyue Li, Yuejie Chi
Main Conference Track
Your Transformer May Not be as Powerful as You Expect Shengjie Luo, Shanda Li, Shuxin Zheng, Tie-Yan Liu, Liwei Wang, Di He
Main Conference Track
Redundancy-Free Message Passing for Graph Neural Networks Rongqin Chen, Shenghui Zhang, Leong Hou U, Ye Li
Main Conference Track
Diffusion-LM Improves Controllable Text Generation Xiang Li, John Thickstun, Ishaan Gulrajani, Percy Liang, Tatsunori B Hashimoto
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Making Sense of Dependence: Efficient Black-box Explanations Using Dependence Measure Paul Novello, Thomas FEL, David Vigouroux
Main Conference Track
Energy-Based Contrastive Learning of Visual Representations Beomsu Kim, Jong Chul Ye
Main Conference Track
Why Robust Generalization in Deep Learning is Difficult: Perspective of Expressive Power Binghui Li, Jikai Jin, Han Zhong, John Hopcroft, Liwei Wang
Main Conference Track
Asynchronous Actor-Critic for Multi-Agent Reinforcement Learning Yuchen Xiao, Weihao Tan, Christopher Amato
Main Conference Track
Polynomial Neural Fields for Subband Decomposition and Manipulation Guandao Yang, Sagie Benaim, Varun Jampani, Kyle Genova, Jonathan Barron, Thomas Funkhouser, Bharath Hariharan, Serge Belongie
Main Conference Track
On the Generalizability and Predictability of Recommender Systems Duncan McElfresh, Sujay Khandagale, Jonathan Valverde, John Dickerson, Colin White
Main Conference Track
Optimal Rates for Regularized Conditional Mean Embedding Learning Zhu Li, Dimitri Meunier, Mattes Mollenhauer, Arthur Gretton
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Divert More Attention to Vision-Language Tracking Mingzhe Guo, Zhipeng Zhang, Heng Fan, Liping Jing
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Rethinking Image Restoration for Object Detection Shangquan Sun, Wenqi Ren, Tao Wang, Xiaochun Cao
Main Conference Track
Optimal Brain Compression: A Framework for Accurate Post-Training Quantization and Pruning Elias Frantar, Dan Alistarh
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Challenging Common Assumptions in Convex Reinforcement Learning Mirco Mutti, Riccardo De Santi, Piersilvio De Bartolomeis, Marcello Restelli
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Association Graph Learning for Multi-Task Classification with Category Shifts Jiayi Shen, Zehao Xiao, Xiantong Zhen, Cees Snoek, Marcel Worring
Main Conference Track
Delving into Sequential Patches for Deepfake Detection Jiazhi Guan, Hang Zhou, Zhibin Hong, Errui Ding, Jingdong Wang, Chengbin Quan, Youjian Zhao
Main Conference Track
On the detrimental effect of invariances in the likelihood for variational inference Richard Kurle, Ralf Herbrich, Tim Januschowski, Yuyang (Bernie) Wang, Jan Gasthaus
Main Conference Track
Self-Supervised Learning Through Efference Copies Franz Scherr, Qinghai Guo, Timoleon Moraitis
Main Conference Track
Precise Learning Curves and Higher-Order Scalings for Dot-product Kernel Regression Lechao Xiao, Hong Hu, Theodor Misiakiewicz, Yue Lu, Jeffrey Pennington
Main Conference Track
A Unified Model for Multi-class Anomaly Detection Zhiyuan You, Lei Cui, Yujun Shen, Kai Yang, Xin Lu, Yu Zheng, Xinyi Le
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Constrained GPI for Zero-Shot Transfer in Reinforcement Learning Jaekyeom Kim, Seohong Park, Gunhee Kim
Main Conference Track
UnfoldML: Cost-Aware and Uncertainty-Based Dynamic 2D Prediction for Multi-Stage Classification Yanbo Xu, Alind Khare, Glenn Matlin, Monish Ramadoss, Rishikesan Kamaleswaran, Chao Zhang, Alexey Tumanov
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Generative Status Estimation and Information Decoupling for Image Rain Removal Di Lin, Xin WANG, Jia Shen, Renjie Zhang, Ruonan Liu, Miaohui Wang, Wuyuan Xie, Qing Guo, Ping Li
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Learning with little mixing Ingvar Ziemann, Stephen Tu
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ComGAN: Unsupervised Disentanglement and Segmentation via Image Composition Rui Ding, Kehua Guo, Xiangyuan Zhu, Zheng Wu, Liwei Wang
Main Conference Track
Sparse Winning Tickets are Data-Efficient Image Recognizers Mukund Varma T, Xuxi Chen, Zhenyu Zhang, Tianlong Chen, Subhashini Venugopalan, Zhangyang Wang
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VAEL: Bridging Variational Autoencoders and Probabilistic Logic Programming Eleonora Misino, Giuseppe Marra, Emanuele Sansone
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The alignment property of SGD noise and how it helps select flat minima: A stability analysis Lei Wu, Mingze Wang, Weijie Su
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EvenNet: Ignoring Odd-Hop Neighbors Improves Robustness of Graph Neural Networks Runlin Lei, Zhen Wang, Yaliang Li, Bolin Ding, Zhewei Wei
Main Conference Track
Differentiable Analog Quantum Computing for Optimization and Control Jiaqi Leng, Yuxiang Peng, Yi-Ling Qiao, Ming Lin, Xiaodi Wu
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Promising or Elusive? Unsupervised Object Segmentation from Real-world Single Images Yafei YANG, Bo Yang
Main Conference Track
Efficiently Factorizing Boolean Matrices using Proximal Gradient Descent Sebastian Dalleiger, Jilles Vreeken
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Learning from Future: A Novel Self-Training Framework for Semantic Segmentation Ye Du, Yujun Shen, Haochen Wang, Jingjing Fei, Wei Li, Liwei Wu, Rui Zhao, Zehua Fu, Qingjie LIU
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A Simple and Provably Efficient Algorithm for Asynchronous Federated Contextual Linear Bandits Jiafan He, Tianhao Wang, Yifei Min, Quanquan Gu
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How Powerful are K-hop Message Passing Graph Neural Networks Jiarui Feng, Yixin Chen, Fuhai Li, Anindya Sarkar, Muhan Zhang
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Dynamic Tensor Product Regression Aravind Reddy, Zhao Song, Lichen Zhang
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Generalization Analysis of Message Passing Neural Networks on Large Random Graphs Sohir Maskey, Ron Levie, Yunseok Lee, Gitta Kutyniok
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On Infinite Separations Between Simple and Optimal Mechanisms Alexandros Psomas, Ariel Schvartzman Cohenca, S. Weinberg
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Online Learning and Pricing for Network Revenue Management with Reusable Resources Huiwen Jia, Cong Shi, Siqian Shen
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Learning to Find Proofs and Theorems by Learning to Refine Search Strategies: The Case of Loop Invariant Synthesis Jonathan Laurent, André Platzer
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Exploitability Minimization in Games and Beyond Denizalp Goktas, Amy Greenwald
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Where2comm: Communication-Efficient Collaborative Perception via Spatial Confidence Maps Yue Hu, Shaoheng Fang, Zixing Lei, Yiqi Zhong, Siheng Chen
Main Conference Track
Your Out-of-Distribution Detection Method is Not Robust! Mohammad Azizmalayeri, Arshia Soltani Moakhar, Arman Zarei, Reihaneh Zohrabi, Mohammad Manzuri, Mohammad Hossein Rohban
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Discovering and Overcoming Limitations of Noise-engineered Data-free Knowledge Distillation Piyush Raikwar, Deepak Mishra
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NaturalProver: Grounded Mathematical Proof Generation with Language Models Sean Welleck, Jiacheng Liu, Ximing Lu, Hannaneh Hajishirzi, Yejin Choi
Main Conference Track
Smoothed Online Convex Optimization Based on Discounted-Normal-Predictor Lijun Zhang, Wei Jiang, Jinfeng Yi, Tianbao Yang
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One for All: Simultaneous Metric and Preference Learning over Multiple Users Gregory Canal, Blake Mason, Ramya Korlakai Vinayak, Robert Nowak
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Few-Shot Fast-Adaptive Anomaly Detection Ze Wang, Yipin Zhou, Rui Wang, Tsung-Yu Lin, Ashish Shah, Ser Nam Lim
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SegViT: Semantic Segmentation with Plain Vision Transformers Bowen Zhang, Zhi Tian, Quan Tang, Xiangxiang Chu, Xiaolin Wei, Chunhua Shen, Yifan liu
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Unsupervised Learning From Incomplete Measurements for Inverse Problems Julián Tachella, Dongdong Chen, Mike Davies
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Redeeming intrinsic rewards via constrained optimization Eric Chen, Zhang-Wei Hong, Joni K. Pajarinen, Pulkit Agrawal
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A Unified Evaluation of Textual Backdoor Learning: Frameworks and Benchmarks Ganqu Cui, Lifan Yuan, Bingxiang He, Yangyi Chen, Zhiyuan Liu, Maosong Sun
Datasets and Benchmarks Track
MissDAG: Causal Discovery in the Presence of Missing Data with Continuous Additive Noise Models Erdun Gao, Ignavier Ng, Mingming Gong, Li Shen, Wei Huang, Tongliang Liu, Kun Zhang, Howard Bondell
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Escaping Saddle Points with Bias-Variance Reduced Local Perturbed SGD for Communication Efficient Nonconvex Distributed Learning Tomoya Murata, Taiji Suzuki
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AttCAT: Explaining Transformers via Attentive Class Activation Tokens Yao Qiang, Deng Pan, Chengyin Li, Xin Li, Rhongho Jang, Dongxiao Zhu
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A Theoretical Study on Solving Continual Learning Gyuhak Kim, Changnan Xiao, Tatsuya Konishi, Zixuan Ke, Bing Liu
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BiMLP: Compact Binary Architectures for Vision Multi-Layer Perceptrons Yixing Xu, Xinghao Chen, Yunhe Wang
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Understanding Deep Neural Function Approximation in Reinforcement Learning via $\epsilon$-Greedy Exploration Fanghui Liu, Luca Viano, Volkan Cevher
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Misspecified Phase Retrieval with Generative Priors Zhaoqiang Liu, Xinshao Wang, Jiulong Liu
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Data-Efficient Augmentation for Training Neural Networks Tian Yu Liu, Baharan Mirzasoleiman
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Divide and Contrast: Source-free Domain Adaptation via Adaptive Contrastive Learning Ziyi Zhang, Weikai Chen, Hui Cheng, Zhen Li, Siyuan Li, Liang Lin, Guanbin Li
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Towards Human-Level Bimanual Dexterous Manipulation with Reinforcement Learning Yuanpei Chen, Tianhao Wu, Shengjie Wang, Xidong Feng, Jiechuan Jiang, Zongqing Lu, Stephen McAleer, Hao Dong, Song-Chun Zhu, Yaodong Yang
Datasets and Benchmarks Track
Outlier-Robust Sparse Mean Estimation for Heavy-Tailed Distributions Ilias Diakonikolas, Daniel Kane, Jasper Lee, Ankit Pensia
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Local-Global MCMC kernels: the best of both worlds Sergey Samsonov, Evgeny Lagutin, Marylou Gabrié, Alain Durmus, Alexey Naumov, Eric Moulines
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The computational and learning benefits of Daleian neural networks Adam Haber, Elad Schneidman
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CLIPDraw: Exploring Text-to-Drawing Synthesis through Language-Image Encoders Kevin Frans, Lisa Soros, Olaf Witkowski
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Chaotic Dynamics are Intrinsic to Neural Network Training with SGD Luis Herrmann, Maximilian Granz, Tim Landgraf
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Efficient and Modular Implicit Differentiation Mathieu Blondel, Quentin Berthet, Marco Cuturi, Roy Frostig, Stephan Hoyer, Felipe Llinares-Lopez, Fabian Pedregosa, Jean-Philippe Vert
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Effective Dimension in Bandit Problems under Censorship Gauthier Guinet, Saurabh Amin, Patrick Jaillet
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Which Explanation Should I Choose? A Function Approximation Perspective to Characterizing Post Hoc Explanations Tessa Han, Suraj Srinivas, Himabindu Lakkaraju
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Accelerating Certified Robustness Training via Knowledge Transfer Pratik Vaishnavi, Kevin Eykholt, Amir Rahmati
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MOMA-LRG: Language-Refined Graphs for Multi-Object Multi-Actor Activity Parsing Zelun Luo, Zane Durante, Linden Li, Wanze Xie, Ruochen Liu, Emily Jin, Zhuoyi Huang, Lun Yu Li, Jiajun Wu, Juan Carlos Niebles, Ehsan Adeli, Fei-Fei Li
Datasets and Benchmarks Track
MTNeuro: A Benchmark for Evaluating Representations of Brain Structure Across Multiple Levels of Abstraction Jorge Quesada, Lakshmi Sathidevi, Ran Liu, Nauman Ahad, Joy Jackson, Mehdi Azabou, Jingyun Xiao, Christopher Liding, Matthew Jin, Carolina Urzay, William Gray-Roncal, Erik Johnson, Eva Dyer
Datasets and Benchmarks Track
FLamby: Datasets and Benchmarks for Cross-Silo Federated Learning in Realistic Healthcare Settings Jean Ogier du Terrail, Samy-Safwan Ayed, Edwige Cyffers, Felix Grimberg, Chaoyang He, Regis Loeb, Paul Mangold, Tanguy Marchand, Othmane Marfoq, Erum Mushtaq, Boris Muzellec, Constantin Philippenko, Santiago Silva, Maria Teleńczuk, Shadi Albarqouni, Salman Avestimehr, Aurélien Bellet, Aymeric Dieuleveut, Martin Jaggi, Sai Praneeth Karimireddy, Marco Lorenzi, Giovanni Neglia, Marc Tommasi, Mathieu Andreux
Datasets and Benchmarks Track
Foundation Posteriors for Approximate Probabilistic Inference Mike Wu, Noah Goodman
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Blackbox Attacks via Surrogate Ensemble Search Zikui Cai, Chengyu Song, Srikanth Krishnamurthy, Amit Roy-Chowdhury, Salman Asif
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Transition to Linearity of General Neural Networks with Directed Acyclic Graph Architecture Libin Zhu, Chaoyue Liu, Misha Belkin
Main Conference Track
A Comprehensive Study on Large-Scale Graph Training: Benchmarking and Rethinking Keyu Duan, Zirui Liu, Peihao Wang, Wenqing Zheng, Kaixiong Zhou, Tianlong Chen, Xia Hu, Zhangyang Wang
Datasets and Benchmarks Track
Scale-invariant Learning by Physics Inversion Philipp Holl, Vladlen Koltun, Nils Thuerey
Main Conference Track
Regret Bounds for Multilabel Classification in Sparse Label Regimes Róbert Busa-Fekete, Heejin Choi, Krzysztof J. Dembczynski, Claudio Gentile, Henry Reeve, Balazs Szorenyi
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Sample Constrained Treatment Effect Estimation Raghavendra Addanki, David Arbour, Tung Mai, Cameron Musco, Anup Rao
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CATER: Intellectual Property Protection on Text Generation APIs via Conditional Watermarks Xuanli He, Qiongkai Xu, Yi Zeng, Lingjuan Lyu, Fangzhao Wu, Jiwei Li, Ruoxi Jia
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On the symmetries of the synchronization problem in Cryo-EM: Multi-Frequency Vector Diffusion Maps on the Projective Plane Gabriele Cesa, Arash Behboodi, Taco S Cohen, Max Welling
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Sketching based Representations for Robust Image Classification with Provable Guarantees Nishanth Dikkala, Sankeerth Rao Karingula, Raghu Meka, Jelani Nelson, Rina Panigrahy, Xin Wang
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ResQ: A Residual Q Function-based Approach for Multi-Agent Reinforcement Learning Value Factorization Siqi Shen, Mengwei Qiu, Jun Liu, Weiquan Liu, Yongquan Fu, Xinwang Liu, Cheng Wang
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Non-identifiability and the Blessings of Misspecification in Models of Molecular Fitness Eli Weinstein, Alan Amin, Jonathan Frazer, Debora Marks
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Conditional Diffusion Process for Inverse Halftoning Hao Jiang, Yadong Mu
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Towards a Standardised Performance Evaluation Protocol for Cooperative MARL Rihab Gorsane, Omayma Mahjoub, Ruan John de Kock, Roland Dubb, Siddarth Singh, Arnu Pretorius
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Size and depth of monotone neural networks: interpolation and approximation Dan Mikulincer, Daniel Reichman
Main Conference Track
Action-modulated midbrain dopamine activity arises from distributed control policies Jack Lindsey, Ashok Litwin-Kumar
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Latent Hierarchical Causal Structure Discovery with Rank Constraints Biwei Huang, Charles Jia Han Low, Feng Xie, Clark Glymour, Kun Zhang
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Beyond Real-world Benchmark Datasets: An Empirical Study of Node Classification with GNNs Seiji Maekawa, Koki Noda, Yuya Sasaki, makoto onizuka
Datasets and Benchmarks Track
Doubly-Asynchronous Value Iteration: Making Value Iteration Asynchronous in Actions Tian Tian, Kenny Young, Richard S. Sutton
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Turbocharging Solution Concepts: Solving NEs, CEs and CCEs with Neural Equilibrium Solvers Luke Marris, Ian Gemp, Thomas Anthony, Andrea Tacchetti, Siqi Liu, Karl Tuyls
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NOMAD: Nonlinear Manifold Decoders for Operator Learning Jacob Seidman, Georgios Kissas, Paris Perdikaris, George J. Pappas
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Semi-Supervised Video Salient Object Detection Based on Uncertainty-Guided Pseudo Labels Yongri Piao, Chenyang Lu, Miao Zhang, Huchuan Lu
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Debiased Causal Tree: Heterogeneous Treatment Effects Estimation with Unmeasured Confounding Caizhi Tang, Huiyuan Wang, Xinyu Li, Qing Cui, Ya-Lin Zhang, Feng Zhu, Longfei Li, Jun Zhou, Linbo Jiang
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Asymptotic Properties for Bayesian Neural Network in Besov Space Kyeongwon Lee, Jaeyong Lee
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A PAC-Bayesian Generalization Bound for Equivariant Networks Arash Behboodi, Gabriele Cesa, Taco S Cohen
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Neural Network Architecture Beyond Width and Depth Shijun Zhang, Zuowei Shen, Haizhao Yang
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S-Prompts Learning with Pre-trained Transformers: An Occam’s Razor for Domain Incremental Learning Yabin Wang, Zhiwu Huang, Xiaopeng Hong
Main Conference Track
OmniVL: One Foundation Model for Image-Language and Video-Language Tasks Junke Wang, Dongdong Chen, Zuxuan Wu, Chong Luo, Luowei Zhou, Yucheng Zhao, Yujia Xie, Ce Liu, Yu-Gang Jiang, Lu Yuan
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Self-Organized Group for Cooperative Multi-agent Reinforcement Learning Jianzhun Shao, Zhiqiang Lou, Hongchang Zhang, Yuhang Jiang, Shuncheng He, Xiangyang Ji
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(Optimal) Online Bipartite Matching with Degree Information Anders Aamand, Justin Chen, Piotr Indyk
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Fairness in Federated Learning via Core-Stability Bhaskar Ray Chaudhury, Linyi Li, Mintong Kang, Bo Li, Ruta Mehta
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Log-Polar Space Convolution Layers Bing Su, Ji-Rong Wen
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CoNSoLe: Convex Neural Symbolic Learning Haoran Li, Yang Weng, Hanghang Tong
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DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Steps Cheng Lu, Yuhao Zhou, Fan Bao, Jianfei Chen, Chongxuan LI, Jun Zhu
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Hierarchical Channel-spatial Encoding for Communication-efficient Collaborative Learning Qihua ZHOU, Song Guo, YI LIU, Jie ZHANG, Jiewei Zhang, Tao GUO, Zhenda XU, Xun Liu, Zhihao Qu
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Attracting and Dispersing: A Simple Approach for Source-free Domain Adaptation Shiqi Yang, yaxing wang, kai wang, Shangling Jui, Joost van de Weijer
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SCINet: Time Series Modeling and Forecasting with Sample Convolution and Interaction Minhao LIU, Ailing Zeng, Muxi Chen, Zhijian Xu, Qiuxia LAI, Lingna Ma, Qiang Xu
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Exploration-Guided Reward Shaping for Reinforcement Learning under Sparse Rewards Rati Devidze, Parameswaran Kamalaruban, Adish Singla
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Active Exploration for Inverse Reinforcement Learning David Lindner, Andreas Krause, Giorgia Ramponi
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Subspace Recovery from Heterogeneous Data with Non-isotropic Noise John C. Duchi, Vitaly Feldman, Lunjia Hu, Kunal Talwar
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Lifelong Neural Predictive Coding: Learning Cumulatively Online without Forgetting Alex Ororbia, Ankur Mali, C Lee Giles, Daniel Kifer
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Align then Fusion: Generalized Large-scale Multi-view Clustering with Anchor Matching Correspondences Siwei Wang, Xinwang Liu, Suyuan Liu, Jiaqi Jin, Wenxuan Tu, Xinzhong Zhu, En Zhu
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Geodesic Graph Neural Network for Efficient Graph Representation Learning Lecheng Kong, Yixin Chen, Muhan Zhang
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Improved Differential Privacy for SGD via Optimal Private Linear Operators on Adaptive Streams Sergey Denisov, H. Brendan McMahan, John Rush, Adam Smith, Abhradeep Guha Thakurta
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On Privacy and Personalization in Cross-Silo Federated Learning Ken Liu, Shengyuan Hu, Steven Z. Wu, Virginia Smith
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SHAQ: Incorporating Shapley Value Theory into Multi-Agent Q-Learning Jianhong Wang, Yuan Zhang, Yunjie Gu, Tae-Kyun Kim
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Trajectory balance: Improved credit assignment in GFlowNets Nikolay Malkin, Moksh Jain, Emmanuel Bengio, Chen Sun, Yoshua Bengio
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Instance-Dependent Near-Optimal Policy Identification in Linear MDPs via Online Experiment Design Andrew Wagenmaker, Kevin G. Jamieson
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🏘️ ProcTHOR: Large-Scale Embodied AI Using Procedural Generation Matt Deitke, Eli VanderBilt, Alvaro Herrasti, Luca Weihs, Kiana Ehsani, Jordi Salvador, Winson Han, Eric Kolve, Aniruddha Kembhavi, Roozbeh Mottaghi
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Efficient Sampling on Riemannian Manifolds via Langevin MCMC Xiang Cheng, Jingzhao Zhang, Suvrit Sra
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OpenFWI: Large-scale Multi-structural Benchmark Datasets for Full Waveform Inversion Chengyuan Deng, Shihang Feng, Hanchen Wang, Xitong Zhang, Peng Jin, Yinan Feng, Qili Zeng, Yinpeng Chen, Youzuo Lin
Datasets and Benchmarks Track
High-Order Pooling for Graph Neural Networks with Tensor Decomposition Chenqing Hua, Guillaume Rabusseau, Jian Tang
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Natural image synthesis for the retina with variational information bottleneck representation Babak Rahmani, Demetri Psaltis, Christophe Moser
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Imitating Past Successes can be Very Suboptimal Benjamin Eysenbach, Soumith Udatha, Ruslan Salakhutdinov, Sergey Levine
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A Communication-efficient Algorithm with Linear Convergence for Federated Minimax Learning Zhenyu Sun, Ermin Wei
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Dynamic Graph Neural Networks Under Spatio-Temporal Distribution Shift Zeyang Zhang, Xin Wang, Ziwei Zhang, Haoyang Li, Zhou Qin, Wenwu Zhu
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Biologically Inspired Dynamic Thresholds for Spiking Neural Networks Jianchuan Ding, Bo Dong, Felix Heide, Yufei Ding, Yunduo Zhou, Baocai Yin, Xin Yang
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GraphQNTK: Quantum Neural Tangent Kernel for Graph Data Yehui Tang, Junchi Yan
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Trajectory-guided Control Prediction for End-to-end Autonomous Driving: A Simple yet Strong Baseline Penghao Wu, Xiaosong Jia, Li Chen, Junchi Yan, Hongyang Li, Yu Qiao
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360-MLC: Multi-view Layout Consistency for Self-training and Hyper-parameter Tuning Bolivar Solarte, Chin-Hsuan Wu, Yueh-Cheng Liu, Yi-Hsuan Tsai, Min Sun
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Distributed Optimization for Overparameterized Problems: Achieving Optimal Dimension Independent Communication Complexity Bingqing Song, Ioannis Tsaknakis, Chung-Yiu Yau, Hoi-To Wai, Mingyi Hong
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Falsification before Extrapolation in Causal Effect Estimation Zeshan M Hussain, Michael Oberst, Ming-Chieh Shih, David Sontag
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Surprise Minimizing Multi-Agent Learning with Energy-based Models Karush Suri, Xiao Qi Shi, Konstantinos N Plataniotis, Yuri Lawryshyn
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Geodesic Self-Attention for 3D Point Clouds Zhengyu Li, XUAN TANG, Zihao Xu, Xihao Wang, Hui Yu, Mingsong Chen, xian wei
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Test Time Adaptation via Conjugate Pseudo-labels Sachin Goyal, Mingjie Sun, Aditi Raghunathan, J. Zico Kolter
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SPD domain-specific batch normalization to crack interpretable unsupervised domain adaptation in EEG Reinmar Kobler, Jun-ichiro Hirayama, Qibin Zhao, Motoaki Kawanabe
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AVLEN: Audio-Visual-Language Embodied Navigation in 3D Environments Sudipta Paul, Amit Roy-Chowdhury, Anoop Cherian
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Semantic uncertainty intervals for disentangled latent spaces Swami Sankaranarayanan, Anastasios Angelopoulos, Stephen Bates, Yaniv Romano, Phillip Isola
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A Fast Scale-Invariant Algorithm for Non-negative Least Squares with Non-negative Data Jelena Diakonikolas, Chenghui Li, Swati Padmanabhan, Chaobing Song
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Self-supervised Amodal Video Object Segmentation Jian Yao, Yuxin Hong, Chiyu Wang, Tianjun Xiao, Tong He, Francesco Locatello, David P Wipf, Yanwei Fu, Zheng Zhang
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Beyond the Return: Off-policy Function Estimation under User-specified Error-measuring Distributions Audrey Huang, Nan Jiang
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Disentangling Transfer in Continual Reinforcement Learning Maciej Wolczyk, Michał Zając, Razvan Pascanu, Łukasz Kuciński, Piotr Miłoś
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Meta-Learning with Self-Improving Momentum Target Jihoon Tack, Jongjin Park, Hankook Lee, Jaeho Lee, Jinwoo Shin
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Online Allocation and Learning in the Presence of Strategic Agents Steven Yin, Shipra Agrawal, Assaf J. Zeevi
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Learning Contrastive Embedding in Low-Dimensional Space Shuo Chen, Chen Gong, Jun Li, Jian Yang, Gang Niu, Masashi Sugiyama
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Near-Optimal Randomized Exploration for Tabular Markov Decision Processes Zhihan Xiong, Ruoqi Shen, Qiwen Cui, Maryam Fazel, Simon S Du
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Defending Against Adversarial Attacks via Neural Dynamic System Xiyuan Li, Zou Xin, Weiwei Liu
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On the Robustness of Graph Neural Diffusion to Topology Perturbations Yang Song, Qiyu Kang, Sijie Wang, Kai Zhao, Wee Peng Tay
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Few-shot Relational Reasoning via Connection Subgraph Pretraining Qian Huang, Hongyu Ren, Jure Leskovec
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Equivariant Networks for Zero-Shot Coordination Darius Muglich, Christian Schroeder de Witt, Elise van der Pol, Shimon Whiteson, Jakob Foerster
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Randomized Sketches for Clustering: Fast and Optimal Kernel $k$-Means Rong Yin, Yong Liu, Weiping Wang, Dan Meng
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Quantile Constrained Reinforcement Learning: A Reinforcement Learning Framework Constraining Outage Probability Whiyoung Jung, Myungsik Cho, Jongeui Park, Youngchul Sung
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Procedural Image Programs for Representation Learning Manel Baradad, Richard Chen, Jonas Wulff, Tongzhou Wang, Rogerio Feris, Antonio Torralba, Phillip Isola
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RényiCL: Contrastive Representation Learning with Skew Rényi Divergence Kyungmin Lee, Jinwoo Shin
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On the Efficient Implementation of High Accuracy Optimality of Profile Maximum Likelihood Moses Charikar, Zhihao Jiang, Kirankumar Shiragur, Aaron Sidford
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Paraphrasing Is All You Need for Novel Object Captioning Cheng-Fu Yang, Yao-Hung Hubert Tsai, Wan-Cyuan Fan, Ruslan Salakhutdinov, Louis-Philippe Morency, Frank Wang
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Adversarial Robustness is at Odds with Lazy Training Yunjuan Wang, Enayat Ullah, Poorya Mianjy, Raman Arora
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Uncertainty Estimation for Multi-view Data: The Power of Seeing the Whole Picture Myong Chol Jung, He Zhao, Joanna Dipnall, Belinda Gabbe, Lan Du
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Motion Transformer with Global Intention Localization and Local Movement Refinement Shaoshuai Shi, Li Jiang, Dengxin Dai, Bernt Schiele
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No-regret learning in games with noisy feedback: Faster rates and adaptivity via learning rate separation Yu-Guan Hsieh, Kimon Antonakopoulos, Volkan Cevher, Panayotis Mertikopoulos
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First-Order Algorithms for Min-Max Optimization in Geodesic Metric Spaces Michael I. Jordan, Tianyi Lin, Emmanouil-Vasileios Vlatakis-Gkaragkounis
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Feature-Proxy Transformer for Few-Shot Segmentation Jian-Wei Zhang, Yifan Sun, Yi Yang, Wei Chen
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Conformal Frequency Estimation with Sketched Data Matteo Sesia, Stefano Favaro
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Revisiting Active Sets for Gaussian Process Decoders Pablo Moreno-Muñoz, Cilie Feldager, Søren Hauberg
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Exact learning dynamics of deep linear networks with prior knowledge Lukas Braun, Clémentine Dominé, James Fitzgerald, Andrew Saxe
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AMP: Automatically Finding Model Parallel Strategies with Heterogeneity Awareness Dacheng Li, Hongyi Wang, Eric P. Xing, Hao Zhang
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A consistently adaptive trust-region method Fadi Hamad, Oliver Hinder
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Online Neural Sequence Detection with Hierarchical Dirichlet Point Process Weihan Li, Yu Qi, Gang Pan
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Leveraging Inter-Layer Dependency for Post -Training Quantization changbao wang, DanDan Zheng, Yuanliu Liu, Liang Li
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Emergence of Hierarchical Layers in a Single Sheet of Self-Organizing Spiking Neurons Paul Bertens, Seong-Whan Lee
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A gradient sampling method with complexity guarantees for Lipschitz functions in high and low dimensions Damek Davis, Dmitriy Drusvyatskiy, Yin Tat Lee, Swati Padmanabhan, Guanghao Ye
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CyCLIP: Cyclic Contrastive Language-Image Pretraining Shashank Goel, Hritik Bansal, Sumit Bhatia, Ryan Rossi, Vishwa Vinay, Aditya Grover
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When does dough become a bagel? Analyzing the remaining mistakes on ImageNet Vijay Vasudevan, Benjamin Caine, Raphael Gontijo Lopes, Sara Fridovich-Keil, Rebecca Roelofs
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Spatial Pruned Sparse Convolution for Efficient 3D Object Detection Jianhui Liu, Yukang Chen, Xiaoqing Ye, Zhuotao Tian, Xiao Tan, Xiaojuan Qi
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Sampling without Replacement Leads to Faster Rates in Finite-Sum Minimax Optimization Aniket Das, Bernhard Schölkopf, Michael Muehlebach
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Feature Learning in $L_2$-regularized DNNs: Attraction/Repulsion and Sparsity Arthur Jacot, Eugene Golikov, Clement Hongler, Franck Gabriel
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Set-based Meta-Interpolation for Few-Task Meta-Learning Seanie Lee, Bruno Andreis, Kenji Kawaguchi, Juho Lee, Sung Ju Hwang
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Non-deep Networks Ankit Goyal, Alexey Bochkovskiy, Jia Deng, Vladlen Koltun
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Low-rank Optimal Transport: Approximation, Statistics and Debiasing Meyer Scetbon, Marco Cuturi
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Embodied Scene-aware Human Pose Estimation Zhengyi Luo, Shun Iwase, Ye Yuan, Kris Kitani
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Privacy Induces Robustness: Information-Computation Gaps and Sparse Mean Estimation Kristian Georgiev, Samuel Hopkins
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Batch Bayesian Optimization on Permutations using the Acquisition Weighted Kernel Changyong Oh, Roberto Bondesan, Efstratios Gavves, Max Welling
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Supervised Training of Conditional Monge Maps Charlotte Bunne, Andreas Krause, Marco Cuturi
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Formalizing Consistency and Coherence of Representation Learning Harald Strömfelt, Luke Dickens, Artur Garcez, Alessandra Russo
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Positively Weighted Kernel Quadrature via Subsampling Satoshi Hayakawa, Harald Oberhauser, Terry Lyons
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Guaranteed Conservation of Momentum for Learning Particle-based Fluid Dynamics Lukas Prantl, Benjamin Ummenhofer, Vladlen Koltun, Nils Thuerey
Main Conference Track
M4Singer: A Multi-Style, Multi-Singer and Musical Score Provided Mandarin Singing Corpus Lichao Zhang, Ruiqi Li, Shoutong Wang, Liqun Deng, Jinglin Liu, Yi Ren, Jinzheng He, Rongjie Huang, Jieming Zhu, Xiao Chen, Zhou Zhao
Datasets and Benchmarks Track
Bayesian Spline Learning for Equation Discovery of Nonlinear Dynamics with Quantified Uncertainty Luning Sun, Daniel Huang, Hao Sun, Jian-Xun Wang
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Convexity Certificates from Hessians Julien Klaus, Niklas Merk, Konstantin Wiedom, Sören Laue, Joachim Giesen
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FR: Folded Rationalization with a Unified Encoder Wei Liu, Haozhao Wang, Jun Wang, Ruixuan Li, Chao Yue, YuanKai Zhang
Main Conference Track
Max-Min Off-Policy Actor-Critic Method Focusing on Worst-Case Robustness to Model Misspecification Takumi Tanabe, Rei Sato, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto
Main Conference Track
One-Inlier is First: Towards Efficient Position Encoding for Point Cloud Registration Fan Yang, Lin Guo, Zhi Chen, Wenbing Tao
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Adaptive Distribution Calibration for Few-Shot Learning with Hierarchical Optimal Transport Dandan Guo, Long Tian, He Zhao, Mingyuan Zhou, Hongyuan Zha
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InsNet: An Efficient, Flexible, and Performant Insertion-based Text Generation Model Sidi Lu, Tao Meng, Nanyun Peng
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Weighted Distillation with Unlabeled Examples Fotis Iliopoulos, Vasilis Kontonis, Cenk Baykal, Gaurav Menghani, Khoa Trinh, Erik Vee
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When Does Group Invariant Learning Survive Spurious Correlations? Yimeng Chen, Ruibin Xiong, Zhi-Ming Ma, Yanyan Lan
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SNAKE: Shape-aware Neural 3D Keypoint Field Chengliang Zhong, Peixing You, Xiaoxue Chen, Hao Zhao, Fuchun Sun, Guyue Zhou, Xiaodong Mu, Chuang Gan, Wenbing Huang
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Single Loop Gaussian Homotopy Method for Non-convex Optimization Hidenori Iwakiri, Yuhang Wang, Shinji Ito, Akiko Takeda
Main Conference Track
Minimax Optimal Online Imitation Learning via Replay Estimation Gokul Swamy, Nived Rajaraman, Matt Peng, Sanjiban Choudhury, J. A. Bagnell, Steven Z. Wu, Jiantao Jiao, Kannan Ramchandran
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Multi-layer State Evolution Under Random Convolutional Design Mara Daniels, Cedric Gerbelot, Florent Krzakala, Lenka Zdeborová
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Mixture-of-Experts with Expert Choice Routing Yanqi Zhou, Tao Lei, Hanxiao Liu, Nan Du, Yanping Huang, Vincent Zhao, Andrew M Dai, zhifeng Chen, Quoc V Le, James Laudon
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GULP: a prediction-based metric between representations Enric Boix-Adsera, Hannah Lawrence, George Stepaniants, Philippe Rigollet
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On the convergence of policy gradient methods to Nash equilibria in general stochastic games Angeliki Giannou, Kyriakos Lotidis, Panayotis Mertikopoulos, Emmanouil-Vasileios Vlatakis-Gkaragkounis
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SAGDA: Achieving $\mathcal{O}(\epsilon^{-2})$ Communication Complexity in Federated Min-Max Learning Haibo Yang, Zhuqing Liu, Xin Zhang, Jia Liu
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ALMA: Hierarchical Learning for Composite Multi-Agent Tasks Shariq Iqbal, Robby Costales, Fei Sha
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Improved Bounds on Neural Complexity for Representing Piecewise Linear Functions Kuan-Lin Chen, Harinath Garudadri, Bhaskar D Rao
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Assaying Out-Of-Distribution Generalization in Transfer Learning Florian Wenzel, Andrea Dittadi, Peter V. Gehler, Carl-Johann Simon-Gabriel, Max Horn, Dominik Zietlow, David Kernert, Chris Russell, Thomas Brox, Bernt Schiele, Bernhard Schölkopf, Francesco Locatello
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M2N: Mesh Movement Networks for PDE Solvers Wenbin Song, Mingrui Zhang, Joseph G Wallwork, Junpeng Gao, Zheng Tian, Fanglei Sun, Matthew Piggott, Junqing Chen, Zuoqiang Shi, Xiang Chen, Jun Wang
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Physics-Informed Implicit Representations of Equilibrium Network Flows Kevin D. Smith, Francesco Seccamonte, Ananthram Swami, Francesco Bullo
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Learning Interface Conditions in Domain Decomposition Solvers Ali Taghibakhshi, Nicolas Nytko, Tareq Uz Zaman, Scott MacLachlan, Luke Olson, Matthew West
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TANKBind: Trigonometry-Aware Neural NetworKs for Drug-Protein Binding Structure Prediction Wei Lu, Qifeng Wu, Jixian Zhang, Jiahua Rao, Chengtao Li, Shuangjia Zheng
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Hamiltonian Latent Operators for content and motion disentanglement in image sequences Asif Khan, Amos J. Storkey
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Convolutional Neural Networks on Graphs with Chebyshev Approximation, Revisited Mingguo He, Zhewei Wei, Ji-Rong Wen
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A Kernelised Stein Statistic for Assessing Implicit Generative Models Wenkai Xu, Gesine D Reinert
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Fine-Grained Semantically Aligned Vision-Language Pre-Training Juncheng Li, XIN HE, Longhui Wei, Long Qian, Linchao Zhu, Lingxi Xie, Yueting Zhuang, Qi Tian, Siliang Tang
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Fast Distance Oracles for Any Symmetric Norm Yichuan Deng, Zhao Song, OMRI WEINSTEIN, Ruizhe Zhang
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Outlier-Robust Sparse Estimation via Non-Convex Optimization Yu Cheng, Ilias Diakonikolas, Rong Ge, Shivam Gupta, Daniel Kane, Mahdi Soltanolkotabi
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Recurrent Convolutional Neural Networks Learn Succinct Learning Algorithms Surbhi Goel, Sham Kakade, Adam Kalai, Cyril Zhang
Main Conference Track
Navigating Memory Construction by Global Pseudo-Task Simulation for Continual Learning Yejia Liu, Wang Zhu, Shaolei Ren
Main Conference Track
Contact-aware Human Motion Forecasting Wei Mao, miaomiao Liu, Richard I Hartley, Mathieu Salzmann
Main Conference Track
Spectral Bias in Practice: The Role of Function Frequency in Generalization Sara Fridovich-Keil, Raphael Gontijo Lopes, Rebecca Roelofs
Main Conference Track
Out-of-Distribution Detection with An Adaptive Likelihood Ratio on Informative Hierarchical VAE Yewen Li, Chaojie Wang, Xiaobo Xia, Tongliang Liu, xin miao, Bo An
Main Conference Track
FOF: Learning Fourier Occupancy Field for Monocular Real-time Human Reconstruction Qiao Feng, Yebin Liu, Yu-Kun Lai, Jingyu Yang, Kun Li
Main Conference Track
Rate-Optimal Online Convex Optimization in Adaptive Linear Control Asaf Benjamin Cassel, Alon Peled-Cohen, Tomer Koren
Main Conference Track
RTFormer: Efficient Design for Real-Time Semantic Segmentation with Transformer Jian Wang, Chenhui Gou, Qiman Wu, Haocheng Feng, Junyu Han, Errui Ding, Jingdong Wang
Main Conference Track
Staggered Rollout Designs Enable Causal Inference Under Interference Without Network Knowledge Mayleen Cortez, Matthew Eichhorn, Christina Yu
Main Conference Track
Censored Quantile Regression Neural Networks for Distribution-Free Survival Analysis Tim Pearce, Jong-Hyeon Jeong, yichen jia, Jun Zhu
Main Conference Track
Learning Graph-embedded Key-event Back-tracing for Object Tracking in Event Clouds Zhiyu Zhu, Junhui Hou, Xianqiang Lyu
Main Conference Track
Efficient and Near-Optimal Smoothed Online Learning for Generalized Linear Functions Adam Block, Max Simchowitz
Main Conference Track
Systematic improvement of neural network quantum states using Lanczos Hongwei Chen, Douglas Hendry, Phillip Weinberg, Adrian Feiguin
Main Conference Track
Grounded Reinforcement Learning: Learning to Win the Game under Human Commands Shusheng Xu, Huaijie Wang, YI WU
Main Conference Track
Enhance the Visual Representation via Discrete Adversarial Training Xiaofeng Mao, YueFeng Chen, Ranjie Duan, Yao Zhu, Gege Qi, shaokai ye, Xiaodan Li, Rong Zhang, Hui Xue'
Main Conference Track
Trading Off Resource Budgets For Improved Regret Bounds Thomas Orton, Damon Falck
Main Conference Track
Natural Color Fool: Towards Boosting Black-box Unrestricted Attacks Shengming Yuan, Qilong Zhang, Lianli Gao, Yaya Cheng, Jingkuan Song
Main Conference Track
Old can be Gold: Better Gradient Flow can Make Vanilla-GCNs Great Again AJAY JAISWAL, Peihao Wang, Tianlong Chen, Justin Rousseau, Ying Ding, Zhangyang Wang
Main Conference Track
Egocentric Video-Language Pretraining Kevin Qinghong Lin, Jinpeng Wang, Mattia Soldan, Michael Wray, Rui Yan, Eric Z. XU, Difei Gao, Rong-Cheng Tu, Wenzhe Zhao, Weijie Kong, Chengfei Cai, WANG HongFa, Dima Damen, Bernard Ghanem, Wei Liu, Mike Zheng Shou
Main Conference Track
Society of Agents: Regret Bounds of Concurrent Thompson Sampling Yan Chen, Perry Dong, Qinxun Bai, Maria Dimakopoulou, Wei Xu, Zhengyuan Zhou
Main Conference Track
A Non-asymptotic Analysis of Non-parametric Temporal-Difference Learning Eloïse Berthier, Ziad Kobeissi, Francis R. Bach
Main Conference Track
CEIP: Combining Explicit and Implicit Priors for Reinforcement Learning with Demonstrations Kai Yan, Alex Schwing, Yu-Xiong Wang
Main Conference Track
Memorization and Optimization in Deep Neural Networks with Minimum Over-parameterization Simone Bombari, Mohammad Hossein Amani, Marco Mondelli
Main Conference Track
LAMP: Extracting Text from Gradients with Language Model Priors Mislav Balunovic, Dimitar Dimitrov, Nikola Jovanović, Martin Vechev
Main Conference Track
Explainability Via Causal Self-Talk Nicholas A. Roy, Junkyung Kim, Neil Rabinowitz
Main Conference Track
Continual Learning with Evolving Class Ontologies Zhiqiu Lin, Deepak Pathak, Yu-Xiong Wang, Deva Ramanan, Shu Kong
Main Conference Track
A gradient estimator via L1-randomization for online zero-order optimization with two point feedback Arya Akhavan, Evgenii Chzhen, Massimiliano Pontil, Alexandre Tsybakov
Main Conference Track
On the SDEs and Scaling Rules for Adaptive Gradient Algorithms Sadhika Malladi, Kaifeng Lyu, Abhishek Panigrahi, Sanjeev Arora
Main Conference Track
Improving Neural Ordinary Differential Equations with Nesterov's Accelerated Gradient Method Ho Huu Nghia Nguyen, Tan Nguyen, Huyen Vo, Stanley Osher, Thieu Vo
Main Conference Track
VER: Scaling On-Policy RL Leads to the Emergence of Navigation in Embodied Rearrangement Erik Wijmans, Irfan A. Essa, Dhruv Batra
Main Conference Track
Neural Attentive Circuits Martin Weiss, Nasim Rahaman, Francesco Locatello, Chris Pal, Yoshua Bengio, Bernhard Schölkopf, Erran Li Li, Nicolas Ballas
Main Conference Track
CLEVRER-Humans: Describing Physical and Causal Events the Human Way Jiayuan Mao, Xuelin Yang, Xikun Zhang, Noah Goodman, Jiajun Wu
Datasets and Benchmarks Track
3D Concept Grounding on Neural Fields Yining Hong, Yilun Du, Chunru Lin, Josh Tenenbaum, Chuang Gan
Main Conference Track
Evaluating Graph Generative Models with Contrastively Learned Features Hamed Shirzad, Kaveh Hassani, Danica J. Sutherland
Main Conference Track
Path Independent Equilibrium Models Can Better Exploit Test-Time Computation Cem Anil, Ashwini Pokle, Kaiqu Liang, Johannes Treutlein, Yuhuai Wu, Shaojie Bai, J. Zico Kolter, Roger B Grosse
Main Conference Track
Implications of Model Indeterminacy for Explanations of Automated Decisions Marc-Etienne Brunet, Ashton Anderson, Richard S. Zemel
Main Conference Track
Debugging and Explaining Metric Learning Approaches: An Influence Function Based Perspective Ruofan Liu, Yun Lin, XIANGLIN YANG, Jin Song Dong
Main Conference Track
Meta-Reinforcement Learning with Self-Modifying Networks Mathieu Chalvidal, Thomas Serre, Rufin VanRullen
Main Conference Track
FairVFL: A Fair Vertical Federated Learning Framework with Contrastive Adversarial Learning Tao Qi, Fangzhao Wu, Chuhan Wu, Lingjuan Lyu, Tong Xu, Hao Liao, Zhongliang Yang, Yongfeng Huang, Xing Xie
Main Conference Track
Incorporating Bias-aware Margins into Contrastive Loss for Collaborative Filtering An Zhang, Wenchang Ma, Xiang Wang, Tat-Seng Chua
Main Conference Track
Multiview Human Body Reconstruction from Uncalibrated Cameras Zhixuan Yu, Linguang Zhang, Yuanlu Xu, Chengcheng Tang, LUAN TRAN, Cem Keskin, Hyun Soo Park
Main Conference Track
MACK: Multimodal Aligned Conceptual Knowledge for Unpaired Image-text Matching Yan Huang, Yuming Wang, Yunan Zeng, Liang Wang
Main Conference Track
Learning Optical Flow from Continuous Spike Streams Rui Zhao, Ruiqin Xiong, Jing Zhao, Zhaofei Yu, Xiaopeng Fan, Tiejun Huang
Main Conference Track
Improving 3D-aware Image Synthesis with A Geometry-aware Discriminator Zifan Shi, Yinghao Xu, Yujun Shen, Deli Zhao, Qifeng Chen, Dit-Yan Yeung
Main Conference Track
A Consistent and Differentiable Lp Canonical Calibration Error Estimator Teodora Popordanoska, Raphael Sayer, Matthew Blaschko
Main Conference Track
Transform Once: Efficient Operator Learning in Frequency Domain Michael Poli, Stefano Massaroli, Federico Berto, Jinkyoo Park, Tri Dao, Christopher Ré, Stefano Ermon
Main Conference Track
Fused Orthogonal Alternating Least Squares for Tensor Clustering Jiacheng Wang, Dan Nicolae
Main Conference Track
A Solver-free Framework for Scalable Learning in Neural ILP Architectures Yatin Nandwani, Rishabh Ranjan, - Mausam, Parag Singla
Main Conference Track
Distributed Distributionally Robust Optimization with Non-Convex Objectives Yang Jiao, Kai Yang, Dongjin Song
Main Conference Track
Parameter-free Regret in High Probability with Heavy Tails Jiujia Zhang, Ashok Cutkosky
Main Conference Track
Non-Convex Bilevel Games with Critical Point Selection Maps Michael Arbel, Julien Mairal
Main Conference Track
Consistent Sufficient Explanations and Minimal Local Rules for explaining the decision of any classifier or regressor Salim I. Amoukou, Nicolas Brunel
Main Conference Track
High-dimensional Additive Gaussian Processes under Monotonicity Constraints Andrés López-Lopera, Francois Bachoc, Olivier Roustant
Main Conference Track
Spherical Channels for Modeling Atomic Interactions Larry Zitnick, Abhishek Das, Adeesh Kolluru, Janice Lan, Muhammed Shuaibi, Anuroop Sriram, Zachary Ulissi, Brandon Wood
Main Conference Track
Handcrafted Backdoors in Deep Neural Networks Sanghyun Hong, Nicholas Carlini, Alexey Kurakin
Main Conference Track
Touch and Go: Learning from Human-Collected Vision and Touch Fengyu Yang, Chenyang Ma, Jiacheng Zhang, Jing Zhu, Wenzhen Yuan, Andrew Owens
Datasets and Benchmarks Track
SoLar: Sinkhorn Label Refinery for Imbalanced Partial-Label Learning Haobo Wang, Mingxuan Xia, Yixuan Li, Yuren Mao, Lei Feng, Gang Chen, Junbo Zhao
Main Conference Track
Log-Linear-Time Gaussian Processes Using Binary Tree Kernels Michael K. Cohen, Samuel Daulton, Michael A Osborne
Main Conference Track
Recovering Private Text in Federated Learning of Language Models Samyak Gupta, Yangsibo Huang, Zexuan Zhong, Tianyu Gao, Kai Li, Danqi Chen
Main Conference Track
INRAS: Implicit Neural Representation for Audio Scenes Kun Su, Mingfei Chen, Eli Shlizerman
Main Conference Track
Non-Monotonic Latent Alignments for CTC-Based Non-Autoregressive Machine Translation Chenze Shao, Yang Feng
Main Conference Track
Attention-based Neural Cellular Automata Mattie Tesfaldet, Derek Nowrouzezahrai, Chris Pal
Main Conference Track
Learning Deep Input-Output Stable Dynamics Ryosuke Kojima, Yuji Okamoto
Main Conference Track
Grounded Video Situation Recognition Zeeshan Khan, C.V. Jawahar, Makarand Tapaswi
Main Conference Track
Policy Optimization with Advantage Regularization for Long-Term Fairness in Decision Systems Eric Yu, Zhizhen Qin, Min Kyung Lee, Sicun Gao
Main Conference Track
Gradient Descent: The Ultimate Optimizer Kartik Chandra, Audrey Xie, Jonathan Ragan-Kelley, ERIK MEIJER
Main Conference Track
DAGMA: Learning DAGs via M-matrices and a Log-Determinant Acyclicity Characterization Kevin Bello, Bryon Aragam, Pradeep K. Ravikumar
Main Conference Track
Forward-Backward Latent State Inference for Hidden Continuous-Time semi-Markov Chains Nicolai Engelmann, Heinz Koeppl
Main Conference Track
LobsDICE: Offline Learning from Observation via Stationary Distribution Correction Estimation Geon-Hyeong Kim, Jongmin Lee, Youngsoo Jang, Hongseok Yang, Kee-Eung Kim
Main Conference Track
Ensemble of Averages: Improving Model Selection and Boosting Performance in Domain Generalization Devansh Arpit, Huan Wang, Yingbo Zhou, Caiming Xiong
Main Conference Track
Is $L^2$ Physics Informed Loss Always Suitable for Training Physics Informed Neural Network? Chuwei Wang, Shanda Li, Di He, Liwei Wang
Main Conference Track
Vision GNN: An Image is Worth Graph of Nodes Kai Han, Yunhe Wang, Jianyuan Guo, Yehui Tang, Enhua Wu
Main Conference Track
ELIGN: Expectation Alignment as a Multi-Agent Intrinsic Reward Zixian Ma, Rose Wang, Fei-Fei Li, Michael Bernstein, Ranjay Krishna
Main Conference Track
Factored DRO: Factored Distributionally Robust Policies for Contextual Bandits Tong Mu, Yash Chandak, Tatsunori B Hashimoto, Emma Brunskill
Main Conference Track
Could Giant Pre-trained Image Models Extract Universal Representations? Yutong Lin, Ze Liu, Zheng Zhang, Han Hu, Nanning Zheng, Stephen Lin, Yue Cao
Main Conference Track
A Scalable Deterministic Global Optimization Algorithm for Training Optimal Decision Tree Kaixun Hua, Jiayang Ren, Yankai Cao
Main Conference Track
Thor: Wielding Hammers to Integrate Language Models and Automated Theorem Provers Albert Qiaochu Jiang, Wenda Li, Szymon Tworkowski, Konrad Czechowski, Tomasz Odrzygóźdź, Piotr Miłoś, Yuhuai Wu, Mateja Jamnik
Main Conference Track
Rethinking Knowledge Graph Evaluation Under the Open-World Assumption Haotong Yang, Zhouchen Lin, Muhan Zhang
Main Conference Track
KERPLE: Kernelized Relative Positional Embedding for Length Extrapolation Ta-Chung Chi, Ting-Han Fan, Peter J Ramadge, Alexander Rudnicky
Main Conference Track
Zonotope Domains for Lagrangian Neural Network Verification Matt Jordan, Jonathan Hayase, Alex Dimakis, Sewoong Oh
Main Conference Track
Neural Basis Models for Interpretability Filip Radenovic, Abhimanyu Dubey, Dhruv Mahajan
Main Conference Track
RecursiveMix: Mixed Learning with History Lingfeng Yang, Xiang Li, Borui Zhao, Renjie Song, Jian Yang
Main Conference Track
GAR: Generalized Autoregression for Multi-Fidelity Fusion Yuxin Wang, Zheng Xing, WEI XING
Main Conference Track
Anonymized Histograms in Intermediate Privacy Models Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi
Main Conference Track
Truly Deterministic Policy Optimization Ehsan Saleh, Saba Ghaffari, Tim Bretl, Matthew West
Main Conference Track
Language Models with Image Descriptors are Strong Few-Shot Video-Language Learners Zhenhailong Wang, Manling Li, Ruochen Xu, Luowei Zhou, Jie Lei, Xudong Lin, Shuohang Wang, Ziyi Yang, Chenguang Zhu, Derek Hoiem, Shih-Fu Chang, Mohit Bansal, Heng Ji
Main Conference Track
3DB: A Framework for Debugging Computer Vision Models Guillaume Leclerc, Hadi Salman, Andrew Ilyas, Sai Vemprala, Logan Engstrom, Vibhav Vineet, Kai Xiao, Pengchuan Zhang, Shibani Santurkar, Greg Yang, Ashish Kapoor, Aleksander Madry
Main Conference Track
Empirical Gateaux Derivatives for Causal Inference Michael I. Jordan, Yixin Wang, Angela Zhou
Main Conference Track
Calibrated Data-Dependent Constraints with Exact Satisfaction Guarantees Songkai Xue, Yuekai Sun, Mikhail Yurochkin
Main Conference Track
Towards Consistency in Adversarial Classification Laurent Meunier, Raphael Ettedgui, Rafael Pinot, Yann Chevaleyre, Jamal Atif
Main Conference Track
Residual Multiplicative Filter Networks for Multiscale Reconstruction Shayan Shekarforoush, David Lindell, David J Fleet, Marcus A Brubaker
Main Conference Track
WT-MVSNet: Window-based Transformers for Multi-view Stereo Jinli Liao, Yikang Ding, Yoli Shavit, Dihe Huang, Shihao Ren, Jia Guo, Wensen Feng, Kai Zhang
Main Conference Track
Private Isotonic Regression Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi
Main Conference Track
A Closer Look at Offline RL Agents Yuwei Fu, Di Wu, Benoit Boulet
Main Conference Track
Generalization Bounds for Estimating Causal Effects of Continuous Treatments Xin Wang, Shengfei Lyu, Xingyu Wu, Tianhao Wu, Huanhuan Chen
Main Conference Track
Better Uncertainty Calibration via Proper Scores for Classification and Beyond Sebastian Gruber, Florian Buettner
Main Conference Track
Video Diffusion Models Jonathan Ho, Tim Salimans, Alexey Gritsenko, William Chan, Mohammad Norouzi, David J Fleet
Main Conference Track
Formulating Robustness Against Unforeseen Attacks Sihui Dai, Saeed Mahloujifar, Prateek Mittal
Main Conference Track
Single Model Uncertainty Estimation via Stochastic Data Centering Jayaraman Thiagarajan, Rushil Anirudh, Vivek Sivaraman Narayanaswamy, Timo Bremer
Main Conference Track
Autoinverse: Uncertainty Aware Inversion of Neural Networks Navid Ansari, Hans-peter Seidel, Nima Vahidi Ferdowsi, Vahid Babaei
Main Conference Track
FedPop: A Bayesian Approach for Personalised Federated Learning Nikita Kotelevskii, Maxime Vono, Alain Durmus, Eric Moulines
Main Conference Track
Semantic Diffusion Network for Semantic Segmentation Haoru Tan, Sitong Wu, Jimin Pi
Main Conference Track
Iterative Structural Inference of Directed Graphs Aoran Wang, Jun Pang
Main Conference Track
An efficient graph generative model for navigating ultra-large combinatorial synthesis libraries Aryan Pedawi, Pawel Gniewek, Chaoyi Chang, Brandon Anderson, Henry van den Bedem
Main Conference Track
Learning to Discover and Detect Objects Vladimir Fomenko, Ismail Elezi, Deva Ramanan, Laura Leal-Taixé, Aljosa Osep
Main Conference Track
Simulation-guided Beam Search for Neural Combinatorial Optimization Jinho Choo, Yeong-Dae Kwon, Jihoon Kim, Jeongwoo Jae, André Hottung, Kevin Tierney, Youngjune Gwon
Main Conference Track
FlowHMM: Flow-based continuous hidden Markov models Pawel Lorek, Rafal Nowak, Tomasz Trzcinski, Maciej Zieba
Main Conference Track
Near Instance-Optimal PAC Reinforcement Learning for Deterministic MDPs Andrea Tirinzoni, Aymen Al Marjani, Emilie Kaufmann
Main Conference Track
VICRegL: Self-Supervised Learning of Local Visual Features Adrien Bardes, Jean Ponce, Yann LeCun
Main Conference Track
Alleviating Adversarial Attacks on Variational Autoencoders with MCMC Anna Kuzina, Max Welling, Jakub Tomczak
Main Conference Track
Policy Gradient With Serial Markov Chain Reasoning Edoardo Cetin, Oya Celiktutan
Main Conference Track
DTG-SSOD: Dense Teacher Guidance for Semi-Supervised Object Detection Gang Li, Xiang Li, Yujie Wang, Wu Yichao, Ding Liang, Shanshan Zhang
Main Conference Track
Human-AI Shared Control via Policy Dissection Quanyi Li, Zhenghao Peng, Haibin Wu, Lan Feng, Bolei Zhou
Main Conference Track
Improving Generative Adversarial Networks via Adversarial Learning in Latent Space Yang Li, Yichuan Mo, Liangliang Shi, Junchi Yan
Main Conference Track
ShapeCrafter: A Recursive Text-Conditioned 3D Shape Generation Model Rao Fu, Xiao Zhan, YIWEN CHEN, Daniel Ritchie, Srinath Sridhar
Main Conference Track
SoundSpaces 2.0: A Simulation Platform for Visual-Acoustic Learning Changan Chen, Carl Schissler, Sanchit Garg, Philip Kobernik, Alexander Clegg, Paul Calamia, Dhruv Batra, Philip Robinson, Kristen Grauman
Datasets and Benchmarks Track
AutoWS-Bench-101: Benchmarking Automated Weak Supervision with 100 Labels Nicholas Roberts, Xintong Li, Tzu-Heng Huang, Dyah Adila, Spencer Schoenberg, Cheng-Yu Liu, Lauren Pick, Haotian Ma, Aws Albarghouthi, Frederic Sala
Datasets and Benchmarks Track
Towards Disentangling Information Paths with Coded ResNeXt Apostolos Avranas, Marios Kountouris
Main Conference Track
Time-Conditioned Dances with Simplicial Complexes: Zigzag Filtration Curve based Supra-Hodge Convolution Networks for Time-series Forecasting Yuzhou Chen, Yulia Gel, H. Vincent Poor
Main Conference Track
Are Defenses for Graph Neural Networks Robust? Felix Mujkanovic, Simon Geisler, Stephan Günnemann, Aleksandar Bojchevski
Main Conference Track
GraB: Finding Provably Better Data Permutations than Random Reshuffling Yucheng Lu, Wentao Guo, Christopher M De Sa
Main Conference Track
Amortized Proximal Optimization Juhan Bae, Paul Vicol, Jeff Z. HaoChen, Roger B Grosse
Main Conference Track
A Statistical Online Inference Approach in Averaged Stochastic Approximation Chuhan Xie, Zhihua Zhang
Main Conference Track
SAViT: Structure-Aware Vision Transformer Pruning via Collaborative Optimization Chuanyang Zheng, zheyang li, Kai Zhang, Zhi Yang, Wenming Tan, Jun Xiao, Ye Ren, Shiliang Pu
Main Conference Track
Deciding What to Model: Value-Equivalent Sampling for Reinforcement Learning Dilip Arumugam, Benjamin Van Roy
Main Conference Track
Giga-scale Kernel Matrix-Vector Multiplication on GPU Robert Hu, Siu Lun Chau, Dino Sejdinovic, Joan Glaunès
Main Conference Track
MultiScan: Scalable RGBD scanning for 3D environments with articulated objects Yongsen Mao, Yiming Zhang, Hanxiao Jiang, Angel Chang, Manolis Savva
Main Conference Track
Are GANs overkill for NLP? David Alvarez-Melis, Vikas Garg, Adam Kalai
Main Conference Track
“Why Not Other Classes?”: Towards Class-Contrastive Back-Propagation Explanations Yipei Wang, Xiaoqian Wang
Main Conference Track
Neural Stochastic Control Jingdong Zhang, Qunxi Zhu, Wei LIN
Main Conference Track
Constrained Update Projection Approach to Safe Policy Optimization Long Yang, Jiaming Ji, Juntao Dai, Linrui Zhang, Binbin Zhou, Pengfei Li, Yaodong Yang, Gang Pan
Main Conference Track
DetCLIP: Dictionary-Enriched Visual-Concept Paralleled Pre-training for Open-world Detection Lewei Yao, Jianhua Han, Youpeng Wen, Xiaodan Liang, Dan Xu, Wei Zhang, Zhenguo Li, Chunjing XU, Hang Xu
Main Conference Track
The Sample Complexity of One-Hidden-Layer Neural Networks Gal Vardi, Ohad Shamir, Nati Srebro
Main Conference Track
Learning from Few Samples: Transformation-Invariant SVMs with Composition and Locality at Multiple Scales Tao Liu, P. R. Kumar, Ruida Zhou, Xi Liu
Main Conference Track
Learning Efficient Vision Transformers via Fine-Grained Manifold Distillation Zhiwei Hao, Jianyuan Guo, Ding Jia, Kai Han, Yehui Tang, Chao Zhang, Han Hu, Yunhe Wang
Main Conference Track
Equivariant Graph Hierarchy-Based Neural Networks Jiaqi Han, Wenbing Huang, Tingyang Xu, Yu Rong
Main Conference Track
Learning interacting dynamical systems with latent Gaussian process ODEs Çağatay Yıldız, Melih Kandemir, Barbara Rakitsch
Main Conference Track
OLIVES Dataset: Ophthalmic Labels for Investigating Visual Eye Semantics Mohit Prabhushankar, Kiran Kokilepersaud, Yash-yee Logan, Stephanie Trejo Corona, Ghassan AlRegib, Charles Wykoff
Datasets and Benchmarks Track
Off-Policy Evaluation for Action-Dependent Non-stationary Environments Yash Chandak, Shiv Shankar, Nathaniel Bastian, Bruno da Silva, Emma Brunskill, Philip S. Thomas
Main Conference Track
Fast Mixing of Stochastic Gradient Descent with Normalization and Weight Decay Zhiyuan Li, Tianhao Wang, Dingli Yu
Main Conference Track
OPEN: Orthogonal Propagation with Ego-Network Modeling Liang Yang, Lina Kang, Qiuliang Zhang, Mengzhe Li, bingxin niu, Dongxiao He, Zhen Wang, Chuan Wang, Xiaochun Cao, Yuanfang Guo
Main Conference Track
Beyond the Best: Distribution Functional Estimation in Infinite-Armed Bandits Yifei Wang, Tavor Baharav, Yanjun Han, Jiantao Jiao, David Tse
Main Conference Track
Adversarial training for high-stakes reliability Daniel Ziegler, Seraphina Nix, Lawrence Chan, Tim Bauman, Peter Schmidt-Nielsen, Tao Lin, Adam Scherlis, Noa Nabeshima, Benjamin Weinstein-Raun, Daniel de Haas, Buck Shlegeris, Nate Thomas
Main Conference Track
ELEVATER: A Benchmark and Toolkit for Evaluating Language-Augmented Visual Models Chunyuan Li, Haotian Liu, Liunian Li, Pengchuan Zhang, Jyoti Aneja, Jianwei Yang, Ping Jin, Houdong Hu, Zicheng Liu, Yong Jae Lee, Jianfeng Gao
Datasets and Benchmarks Track
Augmented RBMLE-UCB Approach for Adaptive Control of Linear Quadratic Systems Akshay Mete, Rahul Singh, P. R. Kumar
Main Conference Track
Stochastic Window Transformer for Image Restoration Jie Xiao, Xueyang Fu, Feng Wu, Zheng-Jun Zha
Main Conference Track
Phase Transition from Clean Training to Adversarial Training Yue Xing, Qifan Song, Guang Cheng
Main Conference Track
pFL-Bench: A Comprehensive Benchmark for Personalized Federated Learning Daoyuan Chen, Dawei Gao, Weirui Kuang, Yaliang Li, Bolin Ding
Datasets and Benchmarks Track
Squeezeformer: An Efficient Transformer for Automatic Speech Recognition Sehoon Kim, Amir Gholami, Albert Shaw, Nicholas Lee, Karttikeya Mangalam, Jitendra Malik, Michael W. Mahoney, Kurt Keutzer
Main Conference Track
Deep Generalized Schrödinger Bridge Guan-Horng Liu, Tianrong Chen, Oswin So, Evangelos Theodorou
Main Conference Track
Characterizing the Ventral Visual Stream with Response-Optimized Neural Encoding Models Meenakshi Khosla, Keith Jamison, Amy Kuceyeski, Mert Sabuncu
Main Conference Track
Learning sparse features can lead to overfitting in neural networks Leonardo Petrini, Francesco Cagnetta, Eric Vanden-Eijnden, Matthieu Wyart
Main Conference Track
Public Wisdom Matters! Discourse-Aware Hyperbolic Fourier Co-Attention for Social Text Classification Karish Grover, S M Phaneendra Angara, Md Shad Akhtar, Tanmoy Chakraborty
Main Conference Track
Harmonizing the object recognition strategies of deep neural networks with humans Thomas FEL, Ivan F Rodriguez Rodriguez, Drew Linsley, Thomas Serre
Main Conference Track
Learning Mixed Multinomial Logits with Provable Guarantees Yiqun Hu, David Simchi-Levi, Zhenzhen Yan
Main Conference Track
Defining and Characterizing Reward Gaming Joar Skalse, Nikolaus Howe, Dmitrii Krasheninnikov, David Krueger
Main Conference Track
Learning Distinct and Representative Modes for Image Captioning Qi Chen, Chaorui Deng, Qi Wu
Main Conference Track
Lifting the Information Ratio: An Information-Theoretic Analysis of Thompson Sampling for Contextual Bandits Gergely Neu, Iuliia Olkhovskaia, Matteo Papini, Ludovic Schwartz
Main Conference Track
Is this the Right Neighborhood? Accurate and Query Efficient Model Agnostic Explanations Amit Dhurandhar, Karthikeyan Natesan Ramamurthy, Karthikeyan Shanmugam
Main Conference Track
Object Scene Representation Transformer Mehdi S. M. Sajjadi, Daniel Duckworth, Aravindh Mahendran, Sjoerd van Steenkiste, Filip Pavetic, Mario Lucic, Leonidas Guibas, Klaus Greff, Thomas Kipf
Main Conference Track
Data-Driven Conditional Robust Optimization Abhilash Reddy Chenreddy, Nymisha Bandi, Erick Delage
Main Conference Track
COLD Decoding: Energy-based Constrained Text Generation with Langevin Dynamics Lianhui Qin, Sean Welleck, Daniel Khashabi, Yejin Choi
Main Conference Track
Matching in Multi-arm Bandit with Collision YiRui Zhang, Siwei Wang, Zhixuan Fang
Main Conference Track
Multimodal Contrastive Learning with LIMoE: the Language-Image Mixture of Experts Basil Mustafa, Carlos Riquelme, Joan Puigcerver, Rodolphe Jenatton, Neil Houlsby
Main Conference Track
Few-shot Learning for Feature Selection with Hilbert-Schmidt Independence Criterion Atsutoshi Kumagai, Tomoharu Iwata, Yasutoshi Ida, Yasuhiro Fujiwara
Main Conference Track
Statistical Learning and Inverse Problems: A Stochastic Gradient Approach Yuri Fonseca, Yuri Saporito
Main Conference Track
Hyperparameter Sensitivity in Deep Outlier Detection: Analysis and a Scalable Hyper-Ensemble Solution Xueying Ding, Lingxiao Zhao, Leman Akoglu
Main Conference Track
TVLT: Textless Vision-Language Transformer Zineng Tang, Jaemin Cho, Yixin Nie, Mohit Bansal
Main Conference Track
A Deep Reinforcement Learning Framework for Column Generation Cheng Chi, Amine Aboussalah, Elias Khalil, Juyoung Wang, Zoha Sherkat-Masoumi
Main Conference Track
Learning to Drop Out: An Adversarial Approach to Training Sequence VAEs Djordje Miladinovic, Kumar Shridhar, Kushal Jain, Max Paulus, Joachim M Buhmann, Carl Allen
Main Conference Track
On the Adversarial Robustness of Mixture of Experts Joan Puigcerver, Rodolphe Jenatton, Carlos Riquelme, Pranjal Awasthi, Srinadh Bhojanapalli
Main Conference Track
Safety Guarantees for Neural Network Dynamic Systems via Stochastic Barrier Functions Rayan Mazouz, Karan Muvvala, Akash Ratheesh Babu, Luca Laurenti, Morteza Lahijanian
Main Conference Track
Simple and Optimal Greedy Online Contention Resolution Schemes Vasilis Livanos
Main Conference Track
Composition Theorems for Interactive Differential Privacy Xin Lyu
Main Conference Track
On Margins and Generalisation for Voting Classifiers Felix Biggs, Valentina Zantedeschi, Benjamin Guedj
Main Conference Track
Effective Backdoor Defense by Exploiting Sensitivity of Poisoned Samples Weixin Chen, Baoyuan Wu, Haoqian Wang
Main Conference Track
Rethinking the Reverse-engineering of Trojan Triggers Zhenting Wang, Kai Mei, Hailun Ding, Juan Zhai, Shiqing Ma
Main Conference Track
Antigen-Specific Antibody Design and Optimization with Diffusion-Based Generative Models for Protein Structures Shitong Luo, Yufeng Su, Xingang Peng, Sheng Wang, Jian Peng, Jianzhu Ma
Main Conference Track
Learning single-index models with shallow neural networks Alberto Bietti, Joan Bruna, Clayton Sanford, Min Jae Song
Main Conference Track
Information bottleneck theory of high-dimensional regression: relevancy, efficiency and optimality Vudtiwat Ngampruetikorn, David J Schwab
Main Conference Track
RainNet: A Large-Scale Imagery Dataset and Benchmark for Spatial Precipitation Downscaling Xuanhong Chen, Kairui Feng, Naiyuan Liu, Bingbing Ni, Yifan Lu, Zhengyan Tong, Ziang Liu
Main Conference Track
Dataset Distillation using Neural Feature Regression Yongchao Zhou, Ehsan Nezhadarya, Jimmy Ba
Main Conference Track
ZeroC: A Neuro-Symbolic Model for Zero-shot Concept Recognition and Acquisition at Inference Time Tailin Wu, Megan Tjandrasuwita, Zhengxuan Wu, Xuelin Yang, Kevin Liu, Rok Sosic, Jure Leskovec
Main Conference Track
Theoretically Better and Numerically Faster Distributed Optimization with Smoothness-Aware Quantization Techniques Bokun Wang, Mher Safaryan, Peter Richtarik
Main Conference Track
Sparse Structure Search for Delta Tuning Shengding Hu, Zhen Zhang, Ning Ding, Yadao Wang, Yasheng Wang, Zhiyuan Liu, Maosong Sun
Main Conference Track
On the Safety of Interpretable Machine Learning: A Maximum Deviation Approach Dennis Wei, Rahul Nair, Amit Dhurandhar, Kush R Varshney, Elizabeth Daly, Moninder Singh
Main Conference Track
Non-stationary Transformers: Exploring the Stationarity in Time Series Forecasting Yong Liu, Haixu Wu, Jianmin Wang, Mingsheng Long
Main Conference Track
Risk-Driven Design of Perception Systems Anthony Corso, Sydney Katz, Craig Innes, Xin Du, Subramanian Ramamoorthy, Mykel J Kochenderfer
Main Conference Track
A Simple Approach to Automated Spectral Clustering Jicong Fan, Yiheng Tu, Zhao Zhang, Mingbo Zhao, Haijun Zhang
Main Conference Track
Joint Entropy Search for Multi-Objective Bayesian Optimization Ben Tu, Axel Gandy, Nikolas Kantas, Behrang Shafei
Main Conference Track
Subgroup Robustness Grows On Trees: An Empirical Baseline Investigation Josh Gardner, Zoran Popovic, Ludwig Schmidt
Main Conference Track
Robustness to Unbounded Smoothness of Generalized SignSGD Michael Crawshaw, Mingrui Liu, Francesco Orabona, Wei Zhang, Zhenxun Zhuang
Main Conference Track
GhostNetV2: Enhance Cheap Operation with Long-Range Attention Yehui Tang, Kai Han, Jianyuan Guo, Chang Xu, Chao Xu, Yunhe Wang
Main Conference Track
Analyzing Sharpness along GD Trajectory: Progressive Sharpening and Edge of Stability Zixuan Wang, Zhouzi Li, Jian Li
Main Conference Track
You Never Stop Dancing: Non-freezing Dance Generation via Bank-constrained Manifold Projection Jiangxin Sun, Chunyu Wang, Huang Hu, Hanjiang Lai, Zhi Jin, Jian-Fang Hu
Main Conference Track
Nonnegative Tensor Completion via Integer Optimization Caleb Bugg, Chen Chen, Anil Aswani
Main Conference Track
LION: Latent Point Diffusion Models for 3D Shape Generation xiaohui zeng, Arash Vahdat, Francis Williams, Zan Gojcic, Or Litany, Sanja Fidler, Karsten Kreis
Main Conference Track
Distribution-Informed Neural Networks for Domain Adaptation Regression Jun Wu, Jingrui He, Sheng Wang, Kaiyu Guan, Elizabeth Ainsworth
Main Conference Track
Momentum Adversarial Distillation: Handling Large Distribution Shifts in Data-Free Knowledge Distillation Kien Do, Thai Hung Le, Dung Nguyen, Dang Nguyen, HARIPRIYA HARIKUMAR, Truyen Tran, Santu Rana, Svetha Venkatesh
Main Conference Track
Hard ImageNet: Segmentations for Objects with Strong Spurious Cues Mazda Moayeri, Sahil Singla, Soheil Feizi
Datasets and Benchmarks Track
VideoMAE: Masked Autoencoders are Data-Efficient Learners for Self-Supervised Video Pre-Training Zhan Tong, Yibing Song, Jue Wang, Limin Wang
Main Conference Track
Scalable design of Error-Correcting Output Codes using Discrete Optimization with Graph Coloring Samarth Gupta, Saurabh Amin
Main Conference Track
A New Family of Generalization Bounds Using Samplewise Evaluated CMI Fredrik Hellström, Giuseppe Durisi
Main Conference Track
Maximum-Likelihood Inverse Reinforcement Learning with Finite-Time Guarantees Siliang Zeng, Chenliang Li, Alfredo Garcia, Mingyi Hong
Main Conference Track
Lost in Latent Space: Examining failures of disentangled models at combinatorial generalisation Milton Montero, Jeffrey Bowers, Rui Ponte Costa, Casimir Ludwig, Gaurav Malhotra
Main Conference Track
MultiGuard: Provably Robust Multi-label Classification against Adversarial Examples Jinyuan Jia, Wenjie Qu, Neil Gong
Main Conference Track
On Measuring Excess Capacity in Neural Networks Florian Graf, Sebastian Zeng, Bastian Rieck, Marc Niethammer, Roland Kwitt
Main Conference Track
On Leave-One-Out Conditional Mutual Information For Generalization Mohamad Rida Rammal, Alessandro Achille, Aditya Golatkar, Suhas Diggavi, Stefano Soatto
Main Conference Track
Near-Isometric Properties of Kronecker-Structured Random Tensor Embeddings Qijia Jiang
Main Conference Track
MExMI: Pool-based Active Model Extraction Crossover Membership Inference Yaxin Xiao, Qingqing Ye, Haibo Hu, Huadi Zheng, Chengfang Fang, Jie Shi
Main Conference Track
Parameter-Efficient Masking Networks Yue Bai, Huan Wang, Xu Ma, Yitian Zhang, Zhiqiang Tao, Yun Fu
Main Conference Track
How Sampling Impacts the Robustness of Stochastic Neural Networks Sina Däubener, Asja Fischer
Main Conference Track
Toward Robust Spiking Neural Network Against Adversarial Perturbation LING LIANG, Kaidi Xu, Xing Hu, Lei Deng, Yuan Xie
Main Conference Track
GRASP: Navigating Retrosynthetic Planning with Goal-driven Policy Yemin Yu, Ying Wei, Kun Kuang, Zhengxing Huang, Huaxiu Yao, Fei Wu
Main Conference Track
End-to-end Symbolic Regression with Transformers Pierre-alexandre Kamienny, Stéphane d'Ascoli, Guillaume Lample, Francois Charton
Main Conference Track
Gold-standard solutions to the Schrödinger equation using deep learning: How much physics do we need? Leon Gerard, Michael Scherbela, Philipp Marquetand, Philipp Grohs
Main Conference Track
EcoFormer: Energy-Saving Attention with Linear Complexity Jing Liu, Zizheng Pan, Haoyu He, Jianfei Cai, Bohan Zhuang
Main Conference Track
Wild-Time: A Benchmark of in-the-Wild Distribution Shift over Time Huaxiu Yao, Caroline Choi, Bochuan Cao, Yoonho Lee, Pang Wei W Koh, Chelsea Finn
Datasets and Benchmarks Track
Sound and Complete Causal Identification with Latent Variables Given Local Background Knowledge Tian-Zuo Wang, Tian Qin, Zhi-Hua Zhou
Main Conference Track
A Unified Diversity Measure for Multiagent Reinforcement Learning Zongkai Liu, Chao Yu, Yaodong Yang, peng sun, Zifan Wu, Yuan Li
Main Conference Track
HorNet: Efficient High-Order Spatial Interactions with Recursive Gated Convolutions Yongming Rao, Wenliang Zhao, Yansong Tang, Jie Zhou, Ser Nam Lim, Jiwen Lu
Main Conference Track
Learning Tractable Probabilistic Models from Inconsistent Local Estimates Shasha Jin, Vasundhara Komaragiri, Tahrima Rahman, Vibhav Gogate
Main Conference Track
Decomposed Knowledge Distillation for Class-Incremental Semantic Segmentation Donghyeon Baek, Youngmin Oh, Sanghoon Lee, Junghyup Lee, Bumsub Ham
Main Conference Track
Minimax Optimal Algorithms for Fixed-Budget Best Arm Identification Junpei Komiyama, Taira Tsuchiya, Junya Honda
Main Conference Track
Reduced Representation of Deformation Fields for Effective Non-rigid Shape Matching Ramana Subramanyam Sundararaman, Riccardo Marin, Emanuele Rodolà, Maks Ovsjanikov
Main Conference Track
BEVFusion: A Simple and Robust LiDAR-Camera Fusion Framework Tingting Liang, Hongwei Xie, Kaicheng Yu, Zhongyu Xia, Zhiwei Lin, Yongtao Wang, Tao Tang, Bing Wang, Zhi Tang
Main Conference Track
Automatic Differentiation of Programs with Discrete Randomness Gaurav Arya, Moritz Schauer, Frank Schäfer, Christopher Rackauckas
Main Conference Track
A Closer Look at the Adversarial Robustness of Deep Equilibrium Models Zonghan Yang, Tianyu Pang, Yang Liu
Main Conference Track
Near-Optimal Private and Scalable $k$-Clustering Vincent Cohen-Addad, Alessandro Epasto, Vahab Mirrokni, Shyam Narayanan, Peilin Zhong
Main Conference Track
NS3: Neuro-symbolic Semantic Code Search Shushan Arakelyan, Anna Hakhverdyan, Miltiadis Allamanis, Luis Garcia, Christophe Hauser, Xiang Ren
Main Conference Track
Revisiting Sparse Convolutional Model for Visual Recognition xili dai, Mingyang Li, Pengyuan Zhai, Shengbang Tong, Xingjian Gao, Shao-Lun Huang, Zhihui Zhu, Chong You, Yi Ma
Main Conference Track
Temporal Latent Bottleneck: Synthesis of Fast and Slow Processing Mechanisms in Sequence Learning Aniket Didolkar, Kshitij Gupta, Anirudh Goyal, Nitesh Bharadwaj Gundavarapu, Alex M Lamb, Nan Rosemary Ke, Yoshua Bengio
Main Conference Track
A Near-Optimal Primal-Dual Method for Off-Policy Learning in CMDP Fan Chen, Junyu Zhang, Zaiwen Wen
Main Conference Track
DReS-FL: Dropout-Resilient Secure Federated Learning for Non-IID Clients via Secret Data Sharing Jiawei Shao, Yuchang Sun, Songze Li, Jun Zhang
Main Conference Track
BackdoorBench: A Comprehensive Benchmark of Backdoor Learning Baoyuan Wu, Hongrui Chen, Mingda Zhang, Zihao Zhu, Shaokui Wei, Danni Yuan, Chao Shen
Datasets and Benchmarks Track
REVIVE: Regional Visual Representation Matters in Knowledge-Based Visual Question Answering Yuanze Lin, Yujia Xie, Dongdong Chen, Yichong Xu, Chenguang Zhu, Lu Yuan
Main Conference Track
FedAvg with Fine Tuning: Local Updates Lead to Representation Learning Liam Collins, Hamed Hassani, Aryan Mokhtari, Sanjay Shakkottai
Main Conference Track
Modeling Transitivity and Cyclicity in Directed Graphs via Binary Code Box Embeddings Dongxu Zhang, Michael Boratko, Cameron Musco, Andrew McCallum
Main Conference Track
Generalization Bounds for Gradient Methods via Discrete and Continuous Prior Xuanyuan Luo, Bei Luo, Jian Li
Main Conference Track
On Deep Generative Models for Approximation and Estimation of Distributions on Manifolds Biraj Dahal, Alexander Havrilla, Minshuo Chen, Tuo Zhao, Wenjing Liao
Main Conference Track
Memory Efficient Continual Learning with Transformers Beyza Ermis, Giovanni Zappella, Martin Wistuba, Aditya Rawal, Cedric Archambeau
Main Conference Track
Counterfactual Neural Temporal Point Process for Estimating Causal Influence of Misinformation on Social Media Yizhou Zhang, Defu Cao, Yan Liu
Main Conference Track
Curriculum Reinforcement Learning using Optimal Transport via Gradual Domain Adaptation Peide Huang, Mengdi Xu, Jiacheng Zhu, Laixi Shi, Fei Fang, DING ZHAO
Main Conference Track
Temporally-Consistent Survival Analysis Lucas Maystre, Daniel Russo
Main Conference Track
Symbolic Distillation for Learned TCP Congestion Control S P Sharan, Wenqing Zheng, Kuo-Feng Hsu, Jiarong Xing, Ang Chen, Zhangyang Wang
Main Conference Track
A Probabilistic Graph Coupling View of Dimension Reduction Hugues Van Assel, Thibault Espinasse, Julien Chiquet, Franck Picard
Main Conference Track
Hardness of Noise-Free Learning for Two-Hidden-Layer Neural Networks Sitan Chen, Aravind Gollakota, Adam Klivans, Raghu Meka
Main Conference Track
Convergence beyond the over-parameterized regime using Rayleigh quotients David A. R. Robin, Kevin Scaman, marc lelarge
Main Conference Track
Optimistic Posterior Sampling for Reinforcement Learning with Few Samples and Tight Guarantees Daniil Tiapkin, Denis Belomestny, Daniele Calandriello, Eric Moulines, Remi Munos, Alexey Naumov, Mark Rowland, Michal Valko, Pierre Ménard
Main Conference Track
On Convergence of FedProx: Local Dissimilarity Invariant Bounds, Non-smoothness and Beyond Xiaotong Yuan, Ping Li
Main Conference Track
Can Push-forward Generative Models Fit Multimodal Distributions? Antoine Salmona, Valentin De Bortoli, Julie Delon, Agnes Desolneux
Main Conference Track
Improved Imaging by Invex Regularizers with Global Optima Guarantees Samuel Pinilla, Tingting Mu, Neil Bourne, Jeyan Thiyagalingam
Main Conference Track
The Neural Covariance SDE: Shaped Infinite Depth-and-Width Networks at Initialization Mufan Li, Mihai Nica, Dan Roy
Main Conference Track
Rethinking and Scaling Up Graph Contrastive Learning: An Extremely Efficient Approach with Group Discrimination YIZHEN ZHENG, Shirui Pan, Vincent CS Lee, Yu Zheng, Philip S Yu
Main Conference Track
Diverse Weight Averaging for Out-of-Distribution Generalization Alexandre Rame, Matthieu Kirchmeyer, Thibaud Rahier, Alain Rakotomamonjy, Patrick Gallinari, Matthieu Cord
Main Conference Track
Bivariate Causal Discovery for Categorical Data via Classification with Optimal Label Permutation Yang Ni
Main Conference Track
Phase transitions in when feedback is useful Lokesh Boominathan, Xaq Pitkow
Main Conference Track
Stochastic Second-Order Methods Improve Best-Known Sample Complexity of SGD for Gradient-Dominated Functions Saeed Masiha, Saber Salehkaleybar, Niao He, Negar Kiyavash, Patrick Thiran
Main Conference Track
Posterior and Computational Uncertainty in Gaussian Processes Jonathan Wenger, Geoff Pleiss, Marvin Pförtner, Philipp Hennig, John P. Cunningham
Main Conference Track
Understanding the Evolution of Linear Regions in Deep Reinforcement Learning Setareh Cohan, Nam Hee Kim, David Rolnick, Michiel van de Panne
Main Conference Track
Causal Discovery in Heterogeneous Environments Under the Sparse Mechanism Shift Hypothesis Ronan Perry, Julius von Kügelgen, Bernhard Schölkopf
Main Conference Track
Towards Practical Control of Singular Values of Convolutional Layers Alexandra Senderovich, Ekaterina Bulatova, Anton Obukhov, Maxim Rakhuba
Main Conference Track
Deep Multi-Modal Structural Equations For Causal Effect Estimation With Unstructured Proxies Shachi Deshpande, Kaiwen Wang, Dhruv Sreenivas, Zheng Li, Volodymyr Kuleshov
Main Conference Track
Generic bounds on the approximation error for physics-informed (and) operator learning Tim De Ryck, Siddhartha Mishra
Main Conference Track
Learning Distributions Generated by Single-Layer ReLU Networks in the Presence of Arbitrary Outliers Saikiran Bulusu, Geethu Joseph, M. Cenk Gursoy, Pramod Varshney
Main Conference Track
GenerSpeech: Towards Style Transfer for Generalizable Out-Of-Domain Text-to-Speech Rongjie Huang, Yi Ren, Jinglin Liu, Chenye Cui, Zhou Zhao
Main Conference Track
On Non-Linear operators for Geometric Deep Learning Grégoire Sergeant-Perthuis, Jakob Maier, Joan Bruna, Edouard Oyallon
Main Conference Track
Momentum Aggregation for Private Non-convex ERM Hoang Tran, Ashok Cutkosky
Main Conference Track
Learning in Congestion Games with Bandit Feedback Qiwen Cui, Zhihan Xiong, Maryam Fazel, Simon S Du
Main Conference Track
LOG: Active Model Adaptation for Label-Efficient OOD Generalization Jie-Jing Shao, Lan-Zhe Guo, Xiao-wen Yang, Yu-Feng Li
Main Conference Track
PolarMix: A General Data Augmentation Technique for LiDAR Point Clouds Aoran Xiao, Jiaxing Huang, Dayan Guan, Kaiwen Cui, Shijian Lu, Ling Shao
Main Conference Track
Learning from Distributed Users in Contextual Linear Bandits Without Sharing the Context Osama Hanna, Lin Yang, Christina Fragouli
Main Conference Track
Provably Feedback-Efficient Reinforcement Learning via Active Reward Learning Dingwen Kong, Lin Yang
Main Conference Track
Recurrent Memory Transformer Aydar Bulatov, Yury Kuratov, Mikhail Burtsev
Main Conference Track
Hierarchical Lattice Layer for Partially Monotone Neural Networks Hiroki Yanagisawa, Kohei Miyaguchi, Takayuki Katsuki
Main Conference Track
Class-Dependent Label-Noise Learning with Cycle-Consistency Regularization De Cheng, Yixiong Ning, Nannan Wang, Xinbo Gao, Heng Yang, Yuxuan Du, Bo Han, Tongliang Liu
Main Conference Track
SeqPATE: Differentially Private Text Generation via Knowledge Distillation Zhiliang Tian, Yingxiu Zhao, Ziyue Huang, Yu-Xiang Wang, Nevin L. Zhang, He He
Main Conference Track
Bayesian Persuasion for Algorithmic Recourse Keegan Harris, Valerie Chen, Joon Kim, Ameet Talwalkar, Hoda Heidari, Steven Z. Wu
Main Conference Track
Instance-Based Uncertainty Estimation for Gradient-Boosted Regression Trees Jonathan Brophy, Daniel Lowd
Main Conference Track
Transcormer: Transformer for Sentence Scoring with Sliding Language Modeling Kaitao Song, Yichong Leng, Xu Tan, Yicheng Zou, Tao Qin, Dongsheng Li
Main Conference Track
Models Out of Line: A Fourier Lens on Distribution Shift Robustness Sara Fridovich-Keil, Brian Bartoldson, James Diffenderfer, Bhavya Kailkhura, Timo Bremer
Main Conference Track
Deep Learning Methods for Proximal Inference via Maximum Moment Restriction Benjamin Kompa, David Bellamy, Tom Kolokotrones, james m robins, Andrew Beam
Main Conference Track
Nest Your Adaptive Algorithm for Parameter-Agnostic Nonconvex Minimax Optimization Junchi YANG, Xiang Li, Niao He
Main Conference Track
Brownian Noise Reduction: Maximizing Privacy Subject to Accuracy Constraints Justin Whitehouse, Aaditya Ramdas, Steven Z. Wu, Ryan M Rogers
Main Conference Track
Are AlphaZero-like Agents Robust to Adversarial Perturbations? Li-Cheng Lan, Huan Zhang, Ti-Rong Wu, Meng-Yu Tsai, I-Chen Wu, Cho-Jui Hsieh
Main Conference Track
AnimeSR: Learning Real-World Super-Resolution Models for Animation Videos Yanze Wu, Xintao Wang, GEN LI, Ying Shan
Main Conference Track
On the Spectral Bias of Convolutional Neural Tangent and Gaussian Process Kernels Amnon Geifman, Meirav Galun, David Jacobs, Basri Ronen
Main Conference Track
Fairness Transferability Subject to Bounded Distribution Shift Yatong Chen, Reilly Raab, Jialu Wang, Yang Liu
Main Conference Track
Improving Self-Supervised Learning by Characterizing Idealized Representations Yann Dubois, Stefano Ermon, Tatsunori B Hashimoto, Percy Liang
Main Conference Track
On the difficulty of learning chaotic dynamics with RNNs Jonas Mikhaeil, Zahra Monfared, Daniel Durstewitz
Main Conference Track
SKFlow: Learning Optical Flow with Super Kernels SHANGKUN SUN, Yuanqi Chen, Yu Zhu, Guodong Guo, Ge Li
Main Conference Track
Mingling Foresight with Imagination: Model-Based Cooperative Multi-Agent Reinforcement Learning Zhiwei Xu, dapeng li, Bin Zhang, Yuan Zhan, Yunpeng Baiia, Guoliang Fan
Main Conference Track
End-to-end Stochastic Optimization with Energy-based Model Lingkai Kong, Jiaming Cui, Yuchen Zhuang, Rui Feng, B. Aditya Prakash, Chao Zhang
Main Conference Track
Learning low-dimensional generalizable natural features from retina using a U-net Siwei Wang, Benjamin Hoshal, Elizabeth de Laittre, Olivier Marre, Michael J. Berry II, Stephanie Palmer
Main Conference Track
Split-kl and PAC-Bayes-split-kl Inequalities for Ternary Random Variables Yi-Shan Wu, Yevgeny Seldin
Main Conference Track
Wasserstein $K$-means for clustering probability distributions Yubo Zhuang, Xiaohui Chen, Yun Yang
Main Conference Track
Learning Long-Term Crop Management Strategies with CyclesGym Matteo Turchetta, Luca Corinzia, Scott Sussex, Amanda Burton, Juan Herrera, Ioannis Athanasiadis, Joachim M Buhmann, Andreas Krause
Datasets and Benchmarks Track
Identification, Amplification and Measurement: A bridge to Gaussian Differential Privacy Yi Liu, Ke Sun, Bei Jiang, Linglong Kong
Main Conference Track
MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields Ilyes Batatia, David P Kovacs, Gregor Simm, Christoph Ortner, Gabor Csanyi
Main Conference Track
Follow-the-Perturbed-Leader for Adversarial Markov Decision Processes with Bandit Feedback Yan Dai, Haipeng Luo, Liyu Chen
Main Conference Track
Improving Multi-Task Generalization via Regularizing Spurious Correlation Ziniu Hu, Zhe Zhao, Xinyang Yi, Tiansheng Yao, Lichan Hong, Yizhou Sun, Ed Chi
Main Conference Track
Estimating and Explaining Model Performance When Both Covariates and Labels Shift Lingjiao Chen, Matei Zaharia, James Y Zou
Main Conference Track
Tenrec: A Large-scale Multipurpose Benchmark Dataset for Recommender Systems Guanghu Yuan, Fajie Yuan, Yudong Li, Beibei Kong, Shujie Li, Lei Chen, Min Yang, Chenyun YU, Bo Hu, Zang Li, Yu Xu, Xiaohu Qie
Datasets and Benchmarks Track
Joint Entropy Search For Maximally-Informed Bayesian Optimization Carl Hvarfner, Frank Hutter, Luigi Nardi
Main Conference Track
Provable General Function Class Representation Learning in Multitask Bandits and MDP Rui Lu, Andrew Zhao, Simon S Du, Gao Huang
Main Conference Track
Weighted Mutual Learning with Diversity-Driven Model Compression Miao Zhang, Li Wang, David Campos, Wei Huang, Chenjuan Guo, Bin Yang
Main Conference Track
S2P: State-conditioned Image Synthesis for Data Augmentation in Offline Reinforcement Learning Daesol Cho, Dongseok Shim, H. Jin Kim
Main Conference Track
Neural Collapse with Normalized Features: A Geometric Analysis over the Riemannian Manifold Can Yaras, Peng Wang, Zhihui Zhu, Laura Balzano, Qing Qu
Main Conference Track
Conformalized Fairness via Quantile Regression Meichen Liu, Lei Ding, Dengdeng Yu, Wulong Liu, Linglong Kong, Bei Jiang
Main Conference Track
Efficient Methods for Non-stationary Online Learning Peng Zhao, Yan-Feng Xie, Lijun Zhang, Zhi-Hua Zhou
Main Conference Track
Increasing the Scope as You Learn: Adaptive Bayesian Optimization in Nested Subspaces Leonard Papenmeier, Luigi Nardi, Matthias Poloczek
Main Conference Track
ACIL: Analytic Class-Incremental Learning with Absolute Memorization and Privacy Protection HUIPING ZHUANG, Zhenyu Weng, Hongxin Wei, RENCHUNZI XIE, Kar-Ann Toh, Zhiping Lin
Main Conference Track
MsSVT: Mixed-scale Sparse Voxel Transformer for 3D Object Detection on Point Clouds Shaocong Dong, Lihe Ding, Haiyang Wang, Tingfa Xu, Xinli Xu, Jie Wang, Ziyang Bian, Ying Wang, Jianan Li
Main Conference Track
Deterministic Langevin Monte Carlo with Normalizing Flows for Bayesian Inference Richard Grumitt, Biwei Dai, Uros Seljak
Main Conference Track
Evolution of Neural Tangent Kernels under Benign and Adversarial Training Noel Loo, Ramin Hasani, Alexander Amini, Daniela Rus
Main Conference Track
Zero-Sum Stochastic Stackelberg Games Denizalp Goktas, Sadie Zhao, Amy Greenwald
Main Conference Track
Evaluating Out-of-Distribution Performance on Document Image Classifiers Stefan Larson, Yi Yang Gordon Lim, Yutong Ai, David Kuang, Kevin Leach
Datasets and Benchmarks Track
Distributed Learning of Conditional Quantiles in the Reproducing Kernel Hilbert Space Heng Lian
Main Conference Track
Spatial Mixture-of-Experts Nikoli Dryden, Torsten Hoefler
Main Conference Track
Amortized Mixing Coupling Processes for Clustering Huafeng Liu, Liping Jing
Main Conference Track
Hilbert Distillation for Cross-Dimensionality Networks Dian Qin, Haishuai Wang, Zhe Liu, HONGJIA XU, Sheng Zhou, Jiajun Bu
Main Conference Track
Provably Efficient Offline Multi-agent Reinforcement Learning via Strategy-wise Bonus Qiwen Cui, Simon S Du
Main Conference Track
A Best-of-Both-Worlds Algorithm for Bandits with Delayed Feedback Saeed Masoudian, Julian Zimmert, Yevgeny Seldin
Main Conference Track
LIFT: Language-Interfaced Fine-Tuning for Non-language Machine Learning Tasks Tuan Dinh, Yuchen Zeng, Ruisu Zhang, Ziqian Lin, Michael Gira, Shashank Rajput, Jy-yong Sohn, Dimitris Papailiopoulos, Kangwook Lee
Main Conference Track
Capturing Failures of Large Language Models via Human Cognitive Biases Erik Jones, Jacob Steinhardt
Main Conference Track
Template based Graph Neural Network with Optimal Transport Distances Cédric Vincent-Cuaz, Rémi Flamary, Marco Corneli, Titouan Vayer, Nicolas Courty
Main Conference Track
Knowledge Distillation Improves Graph Structure Augmentation for Graph Neural Networks Lirong Wu, Haitao Lin, Yufei Huang, Stan Z. Li
Main Conference Track
Learning Invariant Graph Representations for Out-of-Distribution Generalization Haoyang Li, Ziwei Zhang, Xin Wang, Wenwu Zhu
Main Conference Track
A Quadrature Rule combining Control Variates and Adaptive Importance Sampling Rémi Leluc, François Portier, Johan Segers, Aigerim Zhuman
Main Conference Track
GAL: Gradient Assisted Learning for Decentralized Multi-Organization Collaborations Enmao Diao, Jie Ding, Vahid Tarokh
Main Conference Track
Direct Advantage Estimation Hsiao-Ru Pan, Nico Gürtler, Alexander Neitz, Bernhard Schölkopf
Main Conference Track
Honor of Kings Arena: an Environment for Generalization in Competitive Reinforcement Learning Hua Wei, Jingxiao Chen, Xiyang Ji, Hongyang Qin, Minwen Deng, Siqin Li, Liang Wang, Weinan Zhang, Yong Yu, Liu Linc, Lanxiao Huang, Deheng Ye, Qiang Fu, Wei Yang
Datasets and Benchmarks Track
On the Symmetries of Deep Learning Models and their Internal Representations Charles Godfrey, Davis Brown, Tegan Emerson, Henry Kvinge
Main Conference Track
TabNAS: Rejection Sampling for Neural Architecture Search on Tabular Datasets Chengrun Yang, Gabriel Bender, Hanxiao Liu, Pieter-Jan Kindermans, Madeleine Udell, Yifeng Lu, Quoc V Le, Da Huang
Main Conference Track
Embed and Emulate: Learning to estimate parameters of dynamical systems with uncertainty quantification Ruoxi Jiang, Rebecca Willett
Main Conference Track
A Differentiable Semantic Metric Approximation in Probabilistic Embedding for Cross-Modal Retrieval Hao Li, Jingkuan Song, Lianli Gao, Pengpeng Zeng, Haonan Zhang, Gongfu Li
Main Conference Track
Friendly Noise against Adversarial Noise: A Powerful Defense against Data Poisoning Attack Tian Yu Liu, Yu Yang, Baharan Mirzasoleiman
Main Conference Track
Dict-TTS: Learning to Pronounce with Prior Dictionary Knowledge for Text-to-Speech Ziyue Jiang, Zhe Su, Zhou Zhao, Qian Yang, Yi Ren, Jinglin Liu, 振辉叶
Main Conference Track
AZ-whiteness test: a test for signal uncorrelation on spatio-temporal graphs Daniele Zambon, Cesare Alippi
Main Conference Track
ViSioNS: Visual Search in Natural Scenes Benchmark Fermín Travi, Gonzalo Ruarte, Gaston Bujia, Juan Esteban Kamienkowski
Datasets and Benchmarks Track
Value Function Decomposition for Iterative Design of Reinforcement Learning Agents James MacGlashan, Evan Archer, Alisa Devlic, Takuma Seno, Craig Sherstan, Peter Wurman, Peter Stone
Main Conference Track
HandMeThat: Human-Robot Communication in Physical and Social Environments Yanming Wan, Jiayuan Mao, Josh Tenenbaum
Datasets and Benchmarks Track
Task-Agnostic Graph Explanations Yaochen Xie, Sumeet Katariya, Xianfeng Tang, Edward Huang, Nikhil Rao, Karthik Subbian, Shuiwang Ji
Main Conference Track
Embrace the Gap: VAEs Perform Independent Mechanism Analysis Patrik Reizinger, Luigi Gresele, Jack Brady, Julius von Kügelgen, Dominik Zietlow, Bernhard Schölkopf, Georg Martius, Wieland Brendel, Michel Besserve
Main Conference Track
Dataset Inference for Self-Supervised Models Adam Dziedzic, Haonan Duan, Muhammad Ahmad Kaleem, Nikita Dhawan, Jonas Guan, Yannis Cattan, Franziska Boenisch, Nicolas Papernot
Main Conference Track
Statistically Meaningful Approximation: a Case Study on Approximating Turing Machines with Transformers Colin Wei, Yining Chen, Tengyu Ma
Main Conference Track
Improved Feature Distillation via Projector Ensemble Yudong Chen, Sen Wang, Jiajun Liu, Xuwei Xu, Frank de Hoog, Zi Huang
Main Conference Track
Does GNN Pretraining Help Molecular Representation? Ruoxi Sun, Hanjun Dai, Adams Wei Yu
Main Conference Track
ULNeF: Untangled Layered Neural Fields for Mix-and-Match Virtual Try-On Igor Santesteban, Miguel Otaduy, Nils Thuerey, Dan Casas
Main Conference Track
Introspective Learning : A Two-Stage approach for Inference in Neural Networks Mohit Prabhushankar, Ghassan AlRegib
Main Conference Track
Bayesian Active Learning with Fully Bayesian Gaussian Processes Christoffer Riis, Francisco Antunes, Frederik Hüttel, Carlos Lima Azevedo, Francisco Pereira
Main Conference Track
E-MAPP: Efficient Multi-Agent Reinforcement Learning with Parallel Program Guidance Can Chang, Ni Mu, Jiajun Wu, Ling Pan, Huazhe Xu
Main Conference Track
In Defense of the Unitary Scalarization for Deep Multi-Task Learning Vitaly Kurin, Alessandro De Palma, Ilya Kostrikov, Shimon Whiteson, Pawan K Mudigonda
Main Conference Track
Flexible Neural Image Compression via Code Editing Chenjian Gao, Tongda Xu, Dailan He, Yan Wang, Hongwei Qin
Main Conference Track
Homomorphic Matrix Completion Xiao-Yang Liu, Zechu (Steven) Li, Xiaodong Wang
Main Conference Track
Spending Thinking Time Wisely: Accelerating MCTS with Virtual Expansions Weirui Ye, Pieter Abbeel, Yang Gao
Main Conference Track
Intrinsic dimensionality estimation using Normalizing Flows Christian Horvat, Jean-Pascal Pfister
Main Conference Track
Moment Distributionally Robust Tree Structured Prediction Yeshu Li, Danyal Saeed, Xinhua Zhang, Brian Ziebart, Kevin Gimpel
Main Conference Track
Minimax Optimal Fixed-Budget Best Arm Identification in Linear Bandits Junwen Yang, Vincent Tan
Main Conference Track
Tempo: Accelerating Transformer-Based Model Training through Memory Footprint Reduction Muralidhar Andoorveedu, Zhanda Zhu, Bojian Zheng, Gennady Pekhimenko
Main Conference Track
I2DFormer: Learning Image to Document Attention for Zero-Shot Image Classification Muhammad Ferjad Naeem, Yongqin Xian, Luc V Gool, Federico Tombari
Main Conference Track
Benchmarking Heterogeneous Treatment Effect Models through the Lens of Interpretability Jonathan Crabbé, Alicia Curth, Ioana Bica, Mihaela van der Schaar
Datasets and Benchmarks Track
AD-DROP: Attribution-Driven Dropout for Robust Language Model Fine-Tuning Tao Yang, JInghao Deng, Xiaojun Quan, Qifan Wang, Shaoliang Nie
Main Conference Track
Reinforced Genetic Algorithm for Structure-based Drug Design Tianfan Fu, Wenhao Gao, Connor Coley, Jimeng Sun
Main Conference Track
A Variational Edge Partition Model for Supervised Graph Representation Learning Yilin He, Chaojie Wang, Hao Zhang, Bo Chen, Mingyuan Zhou
Main Conference Track
Learning Optimal Flows for Non-Equilibrium Importance Sampling Yu Cao, Eric Vanden-Eijnden
Main Conference Track
Decision Trees with Short Explainable Rules Victor Feitosa Souza, Ferdinando Cicalese, Eduardo Laber, Marco Molinaro
Main Conference Track
NAS-Bench-360: Benchmarking Neural Architecture Search on Diverse Tasks Renbo Tu, Nicholas Roberts, Misha Khodak, Junhong Shen, Frederic Sala, Ameet Talwalkar
Datasets and Benchmarks Track
Sparse Fourier Backpropagation in Cryo-EM Reconstruction Dari Kimanius, Kiarash Jamali, Sjors Scheres
Main Conference Track
Modular Flows: Differential Molecular Generation Yogesh Verma, Samuel Kaski, Markus Heinonen, Vikas Garg
Main Conference Track
Anonymous Bandits for Multi-User Systems Hossein Esfandiari, Vahab Mirrokni, Jon Schneider
Main Conference Track
Unsupervised Object Detection Pretraining with Joint Object Priors Generation and Detector Learning Yizhou Wang, Meilin Chen, SHIXIANG TANG, Feng Zhu, Haiyang Yang, LEI BAI, Rui Zhao, Yunfeng Yan, Donglian Qi, Wanli Ouyang
Main Conference Track
Invariance Learning in Deep Neural Networks with Differentiable Laplace Approximations Alexander Immer, Tycho van der Ouderaa, Gunnar Rätsch, Vincent Fortuin, Mark van der Wilk
Main Conference Track
QueryPose: Sparse Multi-Person Pose Regression via Spatial-Aware Part-Level Query Yabo Xiao, Kai Su, Xiaojuan Wang, Dongdong Yu, Lei Jin, Mingshu He, Zehuan Yuan
Main Conference Track
EAGER: Asking and Answering Questions for Automatic Reward Shaping in Language-guided RL Thomas Carta, Pierre-Yves Oudeyer, Olivier Sigaud, Sylvain Lamprier
Main Conference Track
OpenFilter: A Framework to Democratize Research Access to Social Media AR Filters Piera Riccio, Bill Psomas, Francesco Galati, Francisco Escolano, Thomas Hofmann, Nuria Oliver
Datasets and Benchmarks Track
Improving Policy Learning via Language Dynamics Distillation Victor Zhong, Jesse Mu, Luke Zettlemoyer, Edward Grefenstette, Tim Rocktäschel
Main Conference Track
Learning Energy Networks with Generalized Fenchel-Young Losses Mathieu Blondel, Felipe Llinares-Lopez, Robert Dadashi, Leonard Hussenot, Matthieu Geist
Main Conference Track
Interaction-Grounded Learning with Action-Inclusive Feedback Tengyang Xie, Akanksha Saran, Dylan J Foster, Lekan Molu, Ida Momennejad, Nan Jiang, Paul Mineiro, John Langford
Main Conference Track
Making Look-Ahead Active Learning Strategies Feasible with Neural Tangent Kernels Mohamad Amin Mohamadi, Wonho Bae, Danica J. Sutherland
Main Conference Track
The Neural Testbed: Evaluating Joint Predictions Ian Osband, Zheng Wen, Seyed Mohammad Asghari, Vikranth Dwaracherla, Xiuyuan Lu, MORTEZA IBRAHIMI, Dieterich Lawson, Botao Hao, Brendan O'Donoghue, Benjamin Van Roy
Main Conference Track
Learning Dense Object Descriptors from Multiple Views for Low-shot Category Generalization Stefan Stojanov, Anh Thai, Zixuan Huang, James M. Rehg
Main Conference Track
Monte Carlo Tree Descent for Black-Box Optimization Yaoguang Zhai, Sicun Gao
Main Conference Track
Teacher Forcing Recovers Reward Functions for Text Generation Yongchang Hao, Yuxin Liu, Lili Mou
Main Conference Track
Masked Autoencoding for Scalable and Generalizable Decision Making Fangchen Liu, Hao Liu, Aditya Grover, Pieter Abbeel
Main Conference Track
Distributional Reward Estimation for Effective Multi-agent Deep Reinforcement Learning Jifeng Hu, Yanchao Sun, Hechang Chen, Sili Huang, haiyin piao, Yi Chang, Lichao Sun
Main Conference Track
Sampling from Log-Concave Distributions with Infinity-Distance Guarantees Oren Mangoubi, Nisheeth Vishnoi
Main Conference Track
ELASTIC: Numerical Reasoning with Adaptive Symbolic Compiler Jiaxin Zhang, Yashar Moshfeghi
Main Conference Track
Training Spiking Neural Networks with Local Tandem Learning Qu Yang, Jibin Wu, Malu Zhang, Yansong Chua, Xinchao Wang, Haizhou Li
Main Conference Track
FiLM: Frequency improved Legendre Memory Model for Long-term Time Series Forecasting Tian Zhou, Ziqing MA, xue wang, Qingsong Wen, Liang Sun, Tao Yao, Wotao Yin, Rong Jin
Main Conference Track
Differentially Private Linear Sketches: Efficient Implementations and Applications Fuheng Zhao, Dan Qiao, Rachel Redberg, Divyakant Agrawal, Amr El Abbadi, Yu-Xiang Wang
Main Conference Track
Coordinates Are NOT Lonely - Codebook Prior Helps Implicit Neural 3D representations Fukun Yin, Wen Liu, Zilong Huang, Pei Cheng, Tao Chen, Gang Yu
Main Conference Track
Scalable Neural Video Representations with Learnable Positional Features Subin Kim, Sihyun Yu, Jaeho Lee, Jinwoo Shin
Main Conference Track
Data Augmentation MCMC for Bayesian Inference from Privatized Data Nianqiao Ju, Jordan Awan, Ruobin Gong, Vinayak Rao
Main Conference Track
Neural Circuit Architectural Priors for Embodied Control Nikhil Bhattasali, Anthony M Zador, Tatiana Engel
Main Conference Track
Bayesian Optimization over Discrete and Mixed Spaces via Probabilistic Reparameterization Samuel Daulton, Xingchen Wan, David Eriksson, Maximilian Balandat, Michael A Osborne, Eytan Bakshy
Main Conference Track
Learning to Constrain Policy Optimization with Virtual Trust Region Thai Hung Le, Thommen Karimpanal George, Majid Abdolshah, Dung Nguyen, Kien Do, Sunil Gupta, Svetha Venkatesh
Main Conference Track
Verification and search algorithms for causal DAGs Davin Choo, Kirankumar Shiragur, Arnab Bhattacharyya
Main Conference Track
Causally motivated multi-shortcut identification and removal Jiayun Zheng, Maggie Makar
Main Conference Track
Avalon: A Benchmark for RL Generalization Using Procedurally Generated Worlds Joshua Albrecht, Abraham Fetterman, Bryden Fogelman, Ellie Kitanidis, Bartosz Wróblewski, Nicole Seo, Michael Rosenthal, Maksis Knutins, Zack Polizzi, James Simon, Kanjun Qiu
Datasets and Benchmarks Track
Learning Equivariant Segmentation with Instance-Unique Querying Wenguan Wang, James Liang, Dongfang Liu
Main Conference Track
NeuPhysics: Editable Neural Geometry and Physics from Monocular Videos Yi-Ling Qiao, Alexander Gao, Ming Lin
Main Conference Track
Measuring Data Reconstruction Defenses in Collaborative Inference Systems Mengda Yang, Ziang Li, Juan Wang, Hongxin Hu, Ao Ren, Xiaoyang Xu, Wenzhe Yi
Main Conference Track
ZARTS: On Zero-order Optimization for Neural Architecture Search Xiaoxing Wang, Wenxuan Guo, Jianlin Su, Xiaokang Yang, Junchi Yan
Main Conference Track
Make Some Noise: Reliable and Efficient Single-Step Adversarial Training Pau de Jorge Aranda, Adel Bibi, Riccardo Volpi, Amartya Sanyal, Philip Torr, Gregory Rogez, Puneet Dokania
Main Conference Track
Structural Pruning via Latency-Saliency Knapsack Maying Shen, Hongxu Yin, Pavlo Molchanov, Lei Mao, Jianna Liu, Jose M. Alvarez
Main Conference Track
Risk Bounds of Multi-Pass SGD for Least Squares in the Interpolation Regime Difan Zou, Jingfeng Wu, Vladimir Braverman, Quanquan Gu, Sham Kakade
Main Conference Track
Decision-based Black-box Attack Against Vision Transformers via Patch-wise Adversarial Removal Yucheng Shi, Yahong Han, Yu-an Tan, Xiaohui Kuang
Main Conference Track
EfficientFormer: Vision Transformers at MobileNet Speed Yanyu Li, Geng Yuan, Yang Wen, Ju Hu, Georgios Evangelidis, Sergey Tulyakov, Yanzhi Wang, Jian Ren
Main Conference Track
Holomorphic Equilibrium Propagation Computes Exact Gradients Through Finite Size Oscillations Axel Laborieux, Friedemann Zenke
Main Conference Track
Learning Substructure Invariance for Out-of-Distribution Molecular Representations Nianzu Yang, Kaipeng Zeng, Qitian Wu, Xiaosong Jia, Junchi Yan
Main Conference Track
The Dollar Street Dataset: Images Representing the Geographic and Socioeconomic Diversity of the World William Gaviria Rojas, Sudnya Diamos, Keertan Kini, David Kanter, Vijay Janapa Reddi, Cody Coleman
Datasets and Benchmarks Track
LST: Ladder Side-Tuning for Parameter and Memory Efficient Transfer Learning Yi-Lin Sung, Jaemin Cho, Mohit Bansal
Main Conference Track
CGLB: Benchmark Tasks for Continual Graph Learning Xikun Zhang, Dongjin Song, Dacheng Tao
Datasets and Benchmarks Track
Pre-Trained Image Encoder for Generalizable Visual Reinforcement Learning Zhecheng Yuan, Zhengrong Xue, Bo Yuan, Xueqian Wang, YI WU, Yang Gao, Huazhe Xu
Main Conference Track
Amortized Inference for Heterogeneous Reconstruction in Cryo-EM Axel Levy, Gordon Wetzstein, Julien N.P Martel, Frederic Poitevin, Ellen Zhong
Main Conference Track
RKHS-SHAP: Shapley Values for Kernel Methods Siu Lun Chau, Robert Hu, Javier González, Dino Sejdinovic
Main Conference Track
Single-Stage Visual Relationship Learning using Conditional Queries Alakh Desai, Tz-Ying Wu, Subarna Tripathi, Nuno Vasconcelos
Main Conference Track
Unlabelled Sample Compression Schemes for Intersection-Closed Classes and Extremal Classes Joachim Rubinstein, Benjamin I. Rubinstein
Main Conference Track
VCT: A Video Compression Transformer Fabian Mentzer, George D Toderici, David Minnen, Sergi Caelles, Sung Jin Hwang, Mario Lucic, Eirikur Agustsson
Main Conference Track
Amortized Inference for Causal Structure Learning Lars Lorch, Scott Sussex, Jonas Rothfuss, Andreas Krause, Bernhard Schölkopf
Main Conference Track
Emergent Graphical Conventions in a Visual Communication Game Shuwen Qiu, Sirui Xie, Lifeng Fan, Tao Gao, Jungseock Joo, Song-Chun Zhu, Yixin Zhu
Main Conference Track
Repairing Neural Networks by Leaving the Right Past Behind Ryutaro Tanno, Melanie F. Pradier, Aditya Nori, Yingzhen Li
Main Conference Track
Selective compression learning of latent representations for variable-rate image compression Jooyoung Lee, Seyoon Jeong, Munchurl Kim
Main Conference Track
Multi-LexSum: Real-world Summaries of Civil Rights Lawsuits at Multiple Granularities Zejiang Shen, Kyle Lo, Lauren Yu, Nathan Dahlberg, Margo Schlanger, Doug Downey
Datasets and Benchmarks Track
Increasing Confidence in Adversarial Robustness Evaluations Roland S. Zimmermann, Wieland Brendel, Florian Tramer, Nicholas Carlini
Main Conference Track
Local Bayesian optimization via maximizing probability of descent Quan Nguyen, Kaiwen Wu, Jacob Gardner, Roman Garnett
Main Conference Track
Staircase Attention for Recurrent Processing of Sequences Da JU, Stephen Roller, Sainbayar Sukhbaatar, Jason E Weston
Main Conference Track
Causal Inference with Non-IID Data using Linear Graphical Models Chi Zhang, Karthika Mohan, Judea Pearl
Main Conference Track
Data-Driven Offline Decision-Making via Invariant Representation Learning Han Qi, Yi Su, Aviral Kumar, Sergey Levine
Main Conference Track
Untargeted Backdoor Watermark: Towards Harmless and Stealthy Dataset Copyright Protection Yiming Li, Yang Bai, Yong Jiang, Yong Yang, Shu-Tao Xia, Bo Li
Main Conference Track
Learning Symmetric Rules with SATNet Sangho Lim, Eun-Gyeol Oh, Hongseok Yang
Main Conference Track
The Privacy Onion Effect: Memorization is Relative Nicholas Carlini, Matthew Jagielski, Chiyuan Zhang, Nicolas Papernot, Andreas Terzis, Florian Tramer
Main Conference Track
Langevin Autoencoders for Learning Deep Latent Variable Models Shohei Taniguchi, Yusuke Iwasawa, Wataru Kumagai, Yutaka Matsuo
Main Conference Track
Envy-free Policy Teaching to Multiple Agents Jiarui Gan, R Majumdar, Adish Singla, Goran Radanovic
Main Conference Track
Provably Efficient Model-Free Constrained RL with Linear Function Approximation Arnob Ghosh, Xingyu Zhou, Ness Shroff
Main Conference Track
Towards Optimal Communication Complexity in Distributed Non-Convex Optimization Kumar Kshitij Patel, Lingxiao Wang, Blake E Woodworth, Brian Bullins, Nati Srebro
Main Conference Track
Eliciting Thinking Hierarchy without a Prior Yuqing Kong, Yunqi Li, Yubo Zhang, Zhihuan Huang, Jinzhao Wu
Main Conference Track
Fair and Efficient Allocations Without Obvious Manipulations Alexandros Psomas, Paritosh Verma
Main Conference Track
Bridge the Gap Between Architecture Spaces via A Cross-Domain Predictor Yuqiao Liu, Yehui Tang, Zeqiong Lv, Yunhe Wang, Yanan Sun
Main Conference Track
Shield Decentralization for Safe Multi-Agent Reinforcement Learning Daniel Melcer, Christopher Amato, Stavros Tripakis
Main Conference Track
Domain Generalization without Excess Empirical Risk Ozan Sener, Vladlen Koltun
Main Conference Track
Star Temporal Classification: Sequence Modeling with Partially Labeled Data Vineel Pratap, Awni Hannun, Gabriel Synnaeve, Ronan Collobert
Main Conference Track
Signal Processing for Implicit Neural Representations Dejia Xu, Peihao Wang, Yifan Jiang, Zhiwen Fan, Zhangyang Wang
Main Conference Track
Fault-Aware Neural Code Rankers Jeevana Priya Inala, Chenglong Wang, Mei Yang, Andres Codas, Mark Encarnación, Shuvendu Lahiri, Madanlal Musuvathi, Jianfeng Gao
Main Conference Track
Prompt Certified Machine Unlearning with Randomized Gradient Smoothing and Quantization Zijie Zhang, Yang Zhou, Xin Zhao, Tianshi Che, Lingjuan Lyu
Main Conference Track
What Makes a "Good" Data Augmentation in Knowledge Distillation - A Statistical Perspective Huan Wang, Suhas Lohit, Michael N. Jones, Yun Fu
Main Conference Track
Supervising the Multi-Fidelity Race of Hyperparameter Configurations Martin Wistuba, Arlind Kadra, Josif Grabocka
Main Conference Track
Streaming Radiance Fields for 3D Video Synthesis Lingzhi LI, Zhen Shen, Zhongshu Wang, Li Shen, Ping Tan
Main Conference Track
Byzantine-tolerant federated Gaussian process regression for streaming data Xu Zhang, Zhenyuan Yuan, Minghui Zhu
Main Conference Track
Neural Matching Fields: Implicit Representation of Matching Fields for Visual Correspondence Sunghwan Hong, Jisu Nam, Seokju Cho, Susung Hong, Sangryul Jeon, Dongbo Min, Seungryong Kim
Main Conference Track
Consistency of Constrained Spectral Clustering under Graph Induced Fair Planted Partitions Shubham Gupta, Ambedkar Dukkipati
Main Conference Track
Local Spatiotemporal Representation Learning for Longitudinally-consistent Neuroimage Analysis Mengwei Ren, Neel Dey, Martin Styner, Kelly Botteron, Guido Gerig
Main Conference Track
Overparameterization from Computational Constraints Sanjam Garg, Somesh Jha, Saeed Mahloujifar, Mohammad Mahmoody, Mingyuan Wang
Main Conference Track
A Unifying Framework of Off-Policy General Value Function Evaluation Tengyu Xu, Zhuoran Yang, Zhaoran Wang, Yingbin Liang
Main Conference Track
Anchor-Changing Regularized Natural Policy Gradient for Multi-Objective Reinforcement Learning Ruida Zhou, Tao Liu, Dileep Kalathil, P. R. Kumar, Chao Tian
Main Conference Track
Do Current Multi-Task Optimization Methods in Deep Learning Even Help? Derrick Xin, Behrooz Ghorbani, Justin Gilmer, Ankush Garg, Orhan Firat
Main Conference Track
TAP-Vid: A Benchmark for Tracking Any Point in a Video Carl Doersch, Ankush Gupta, Larisa Markeeva, Adria Recasens, Lucas Smaira, Yusuf Aytar, Joao Carreira, Andrew Zisserman, Yi Yang
Datasets and Benchmarks Track
Alignment-guided Temporal Attention for Video Action Recognition Yizhou Zhao, Zhenyang Li, Xun Guo, Yan Lu
Main Conference Track
Meta Reinforcement Learning with Finite Training Tasks - a Density Estimation Approach Zohar Rimon, Aviv Tamar, Gilad Adler
Main Conference Track
TotalSelfScan: Learning Full-body Avatars from Self-Portrait Videos of Faces, Hands, and Bodies Junting Dong, Qi Fang, Yudong Guo, Sida Peng, Qing Shuai, Xiaowei Zhou, Hujun Bao
Main Conference Track
DHRL: A Graph-Based Approach for Long-Horizon and Sparse Hierarchical Reinforcement Learning Seungjae Lee, Jigang Kim, Inkyu Jang, H. Jin Kim
Main Conference Track
A Classification of $G$-invariant Shallow Neural Networks Devanshu Agrawal, James Ostrowski
Main Conference Track
A Conditional Randomization Test for Sparse Logistic Regression in High-Dimension Binh T. Nguyen, Bertrand Thirion, Sylvain Arlot
Main Conference Track
Biologically-Plausible Determinant Maximization Neural Networks for Blind Separation of Correlated Sources Bariscan Bozkurt, Cengiz Pehlevan, Alper Erdogan
Main Conference Track
Generalized One-shot Domain Adaptation of Generative Adversarial Networks Zicheng Zhang, Yinglu Liu, Congying Han, Tiande Guo, Ting Yao, Tao Mei
Main Conference Track
Representing Spatial Trajectories as Distributions Didac Suris Coll-Vinent, Carl Vondrick
Main Conference Track
EPIC-KITCHENS VISOR Benchmark: VIdeo Segmentations and Object Relations Ahmad Darkhalil, Dandan Shan, Bin Zhu, Jian Ma, Amlan Kar, Richard Higgins, Sanja Fidler, David Fouhey, Dima Damen
Datasets and Benchmarks Track
Inverse Design for Fluid-Structure Interactions using Graph Network Simulators Kelsey Allen, Tatiana Lopez-Guevara, Kimberly L Stachenfeld, Alvaro Sanchez Gonzalez, Peter Battaglia, Jessica B Hamrick, Tobias Pfaff
Main Conference Track
What Makes Graph Neural Networks Miscalibrated? Hans Hao-Hsun Hsu, Yuesong Shen, Christian Tomani, Daniel Cremers
Main Conference Track
Stochastic Adaptive Activation Function Kyungsu Lee, Jaeseung Yang, Haeyun Lee, Jae Youn Hwang
Main Conference Track
ActionSense: A Multimodal Dataset and Recording Framework for Human Activities Using Wearable Sensors in a Kitchen Environment Joseph DelPreto, Chao Liu, Yiyue Luo, Michael Foshey, Yunzhu Li, Antonio Torralba, Wojciech Matusik, Daniela Rus
Datasets and Benchmarks Track
Video compression dataset and benchmark of learning-based video-quality metrics Anastasia Antsiferova, Sergey Lavrushkin, Maksim Smirnov, Aleksandr Gushchin, Dmitriy Vatolin, Dmitriy Kulikov
Datasets and Benchmarks Track
Scalable Distributional Robustness in a Class of Non-Convex Optimization with Guarantees Avinandan Bose, Arunesh Sinha, Tien Mai
Main Conference Track
Prototypical VoteNet for Few-Shot 3D Point Cloud Object Detection Shizhen Zhao, Xiaojuan Qi
Main Conference Track
Learning from a Sample in Online Algorithms C.J. Argue, Alan Frieze, Anupam Gupta, Christopher Seiler
Main Conference Track
Robust Rent Division Dominik Peters, Ariel D Procaccia, David Zhu
Main Conference Track
Efficient Dataset Distillation using Random Feature Approximation Noel Loo, Ramin Hasani, Alexander Amini, Daniela Rus
Main Conference Track
Scalable Sensitivity and Uncertainty Analyses for Causal-Effect Estimates of Continuous-Valued Interventions Andrew Jesson, Alyson Douglas, Peter Manshausen, Maëlys Solal, Nicolai Meinshausen, Philip Stier, Yarin Gal, Uri Shalit
Main Conference Track
Sparse Interaction Additive Networks via Feature Interaction Detection and Sparse Selection James Enouen, Yan Liu
Main Conference Track
Faster Stochastic Algorithms for Minimax Optimization under Polyak-{\L}ojasiewicz Condition Lesi Chen, Boyuan Yao, Luo Luo
Main Conference Track
Kantorovich Strikes Back! Wasserstein GANs are not Optimal Transport? Alexander Korotin, Alexander Kolesov, Evgeny Burnaev
Datasets and Benchmarks Track
List-Decodable Sparse Mean Estimation via Difference-of-Pairs Filtering Ilias Diakonikolas, Daniel Kane, Sushrut Karmalkar, Ankit Pensia, Thanasis Pittas
Main Conference Track
Distributional Convergence of the Sliced Wasserstein Process Jiaqi Xi, Jonathan Niles-Weed
Main Conference Track
VTC-LFC: Vision Transformer Compression with Low-Frequency Components Zhenyu Wang, Hao Luo, Pichao WANG, Feng Ding, Fan Wang, Hao Li
Main Conference Track
A Theory of PAC Learnability under Transformation Invariances Han Shao, Omar Montasser, Avrim Blum
Main Conference Track
PALBERT: Teaching ALBERT to Ponder Nikita Balagansky, Daniil Gavrilov
Main Conference Track
Distributed Methods with Compressed Communication for Solving Variational Inequalities, with Theoretical Guarantees Aleksandr Beznosikov, Peter Richtarik, Michael Diskin, Max Ryabinin, Alexander Gasnikov
Main Conference Track
Analyzing Data-Centric Properties for Graph Contrastive Learning Puja Trivedi, Ekdeep S Lubana, Mark Heimann, Danai Koutra, Jayaraman Thiagarajan
Main Conference Track
Learning Bipartite Graphs: Heavy Tails and Multiple Components José Vinícius de Miranda Cardoso, Jiaxi Ying, Daniel Palomar
Main Conference Track
Training Scale-Invariant Neural Networks on the Sphere Can Happen in Three Regimes Maxim Kodryan, Ekaterina Lobacheva, Maksim Nakhodnov, Dmitry P Vetrov
Main Conference Track
Exploring the Whole Rashomon Set of Sparse Decision Trees Rui Xin, Chudi Zhong, Zhi Chen, Takuya Takagi, Margo Seltzer, Cynthia Rudin
Main Conference Track
Graph Self-supervised Learning with Accurate Discrepancy Learning Dongki Kim, Jinheon Baek, Sung Ju Hwang
Main Conference Track
Multi-Scale Adaptive Network for Single Image Denoising Yuanbiao Gou, Peng Hu, Jiancheng Lv, Joey Tianyi Zhou, Xi Peng
Main Conference Track
A theory of weight distribution-constrained learning Weishun Zhong, Ben Sorscher, Daniel D. Lee, Haim Sompolinsky
Main Conference Track
Hierarchical Normalization for Robust Monocular Depth Estimation Chi Zhang, Wei Yin, Billzb Wang, Gang Yu, BIN FU, Chunhua Shen
Main Conference Track
Deep Compression of Pre-trained Transformer Models Naigang Wang, Chi-Chun (Charlie) Liu, Swagath Venkataramani, Sanchari Sen, Chia-Yu Chen, Kaoutar El Maghraoui, Vijayalakshmi (Viji) Srinivasan, Leland Chang
Main Conference Track
Constrained Predictive Coding as a Biologically Plausible Model of the Cortical Hierarchy Siavash Golkar, Tiberiu Tesileanu, Yanis Bahroun, Anirvan Sengupta, Dmitri B. Chklovskii
Main Conference Track
Washing The Unwashable : On The (Im)possibility of Fairwashing Detection Ali Shahin Shamsabadi, Mohammad Yaghini, Natalie Dullerud, Sierra Wyllie, Ulrich Aïvodji, Aisha Alaagib, Sébastien Gambs, Nicolas Papernot
Main Conference Track
Near-Optimal Collaborative Learning in Bandits Clémence Réda, Sattar Vakili, Emilie Kaufmann
Main Conference Track
Hypothesis Testing for Differentially Private Linear Regression Daniel Alabi, Salil Vadhan
Main Conference Track
Bayesian Optimistic Optimization: Optimistic Exploration for Model-based Reinforcement Learning Chenyang Wu, Tianci Li, Zongzhang Zhang, Yang Yu
Main Conference Track
TokenMixup: Efficient Attention-guided Token-level Data Augmentation for Transformers Hyeong Kyu Choi, Joonmyung Choi, Hyunwoo J Kim
Main Conference Track
Error Analysis of Tensor-Train Cross Approximation Zhen Qin, Alexander Lidiak, Zhexuan Gong, Gongguo Tang, Michael B Wakin, Zhihui Zhu
Main Conference Track
Approximate Secular Equations for the Cubic Regularization Subproblem Yihang Gao, Man-Chung Yue, Michael Ng
Main Conference Track
On the Theoretical Properties of Noise Correlation in Stochastic Optimization Aurelien Lucchi, Frank Proske, Antonio Orvieto, Francis R. Bach, Hans Kersting
Main Conference Track
Test-Time Prompt Tuning for Zero-Shot Generalization in Vision-Language Models Manli Shu, Weili Nie, De-An Huang, Zhiding Yu, Tom Goldstein, Anima Anandkumar, Chaowei Xiao
Main Conference Track
SemMAE: Semantic-Guided Masking for Learning Masked Autoencoders Gang Li, Heliang Zheng, Daqing Liu, Chaoyue Wang, Bing Su, Changwen Zheng
Main Conference Track
BiT: Robustly Binarized Multi-distilled Transformer Zechun Liu, Barlas Oguz, Aasish Pappu, Lin Xiao, Scott Yih, Meng Li, Raghuraman Krishnamoorthi, Yashar Mehdad
Main Conference Track
Perturbation Learning Based Anomaly Detection Jinyu Cai, Jicong Fan
Main Conference Track
Knowledge-Aware Bayesian Deep Topic Model Dongsheng Wang, Yi.shi Xu, Miaoge Li, Zhibin Duan, Chaojie Wang, Bo Chen, Mingyuan Zhou
Main Conference Track
SelecMix: Debiased Learning by Contradicting-pair Sampling Inwoo Hwang, Sangjun Lee, Yunhyeok Kwak, Seong Joon Oh, Damien Teney, Jin-Hwa Kim, Byoung-Tak Zhang
Main Conference Track
Are all Frames Equal? Active Sparse Labeling for Video Action Detection Aayush Rana, Yogesh Rawat
Main Conference Track
Unsupervised Domain Adaptation for Semantic Segmentation using Depth Distribution Quanliang Wu, Huajun Liu
Main Conference Track
P2P: Tuning Pre-trained Image Models for Point Cloud Analysis with Point-to-Pixel Prompting Ziyi Wang, Xumin Yu, Yongming Rao, Jie Zhou, Jiwen Lu
Main Conference Track
Finding Differences Between Transformers and ConvNets Using Counterfactual Simulation Testing Nataniel Ruiz, Sarah Bargal, Cihang Xie, Kate Saenko, Stan Sclaroff
Main Conference Track
In the Eye of the Beholder: Robust Prediction with Causal User Modeling Amir Feder, Guy Horowitz, Yoav Wald, Roi Reichart, Nir Rosenfeld
Main Conference Track
Variational inference via Wasserstein gradient flows Marc Lambert, Sinho Chewi, Francis R. Bach, Silvère Bonnabel, Philippe Rigollet
Main Conference Track
projUNN: efficient method for training deep networks with unitary matrices Bobak Kiani, Randall Balestriero, Yann LeCun, Seth Lloyd
Main Conference Track
Reinforcement Learning in a Birth and Death Process: Breaking the Dependence on the State Space Jonatha Anselmi, Bruno Gaujal, Louis-Sébastien Rebuffi
Main Conference Track
Multi-dataset Training of Transformers for Robust Action Recognition Junwei Liang, Enwei Zhang, Jun Zhang, Chunhua Shen
Main Conference Track
An Embarrassingly Simple Approach to Semi-Supervised Few-Shot Learning Xiu-Shen Wei, H.-Y. Xu, Faen Zhang, Yuxin Peng, Wei Zhou
Main Conference Track
Recipe for a General, Powerful, Scalable Graph Transformer Ladislav Rampášek, Michael Galkin, Vijay Prakash Dwivedi, Anh Tuan Luu, Guy Wolf, Dominique Beaini
Main Conference Track
ALIFE: Adaptive Logit Regularizer and Feature Replay for Incremental Semantic Segmentation Youngmin Oh, Donghyeon Baek, Bumsub Ham
Main Conference Track
Rare Gems: Finding Lottery Tickets at Initialization Kartik Sreenivasan, Jy-yong Sohn, Liu Yang, Matthew Grinde, Alliot Nagle, Hongyi Wang, Eric P. Xing, Kangwook Lee, Dimitris Papailiopoulos
Main Conference Track
Fast Vision Transformers with HiLo Attention Zizheng Pan, Jianfei Cai, Bohan Zhuang
Main Conference Track
Online Bipartite Matching with Advice: Tight Robustness-Consistency Tradeoffs for the Two-Stage Model Billy Jin, Will Ma
Main Conference Track
Identifying good directions to escape the NTK regime and efficiently learn low-degree plus sparse polynomials Eshaan Nichani, Yu Bai, Jason Lee
Main Conference Track
Pure Transformers are Powerful Graph Learners Jinwoo Kim, Dat Nguyen, Seonwoo Min, Sungjun Cho, Moontae Lee, Honglak Lee, Seunghoon Hong
Main Conference Track
Orthogonal Transformer: An Efficient Vision Transformer Backbone with Token Orthogonalization Huaibo Huang, Xiaoqiang Zhou, Ran He
Main Conference Track
Using Mixup as a Regularizer Can Surprisingly Improve Accuracy & Out-of-Distribution Robustness Francesco Pinto, Harry Yang, Ser Nam Lim, Philip Torr, Puneet Dokania
Main Conference Track
NeurOLight: A Physics-Agnostic Neural Operator Enabling Parametric Photonic Device Simulation Jiaqi Gu, Zhengqi Gao, Chenghao Feng, Hanqing Zhu, Ray Chen, Duane Boning, David Pan
Main Conference Track
Learning the Structure of Large Networked Systems Obeying Conservation Laws Anirudh Rayas, Rajasekhar Anguluri, Gautam Dasarathy
Main Conference Track
FP8 Quantization: The Power of the Exponent Andrey Kuzmin, Mart van Baalen, Yuwei Ren, Markus Nagel, Jorn Peters, Tijmen Blankevoort
Main Conference Track
Bridging the Gap Between Vision Transformers and Convolutional Neural Networks on Small Datasets Zhiying Lu, Hongtao Xie, Chuanbin Liu, Yongdong Zhang
Main Conference Track
Private Set Generation with Discriminative Information Dingfan Chen, Raouf Kerkouche, Mario Fritz
Main Conference Track
The First Optimal Algorithm for Smooth and Strongly-Convex-Strongly-Concave Minimax Optimization Dmitry Kovalev, Alexander Gasnikov
Main Conference Track
Provable Defense against Backdoor Policies in Reinforcement Learning Shubham Bharti, Xuezhou Zhang, Adish Singla, Xiaojin Zhu
Main Conference Track
Diffusion Models as Plug-and-Play Priors Alexandros Graikos, Nikolay Malkin, Nebojsa Jojic, Dimitris Samaras
Main Conference Track
CoupAlign: Coupling Word-Pixel with Sentence-Mask Alignments for Referring Image Segmentation Zicheng Zhang, Yi Zhu, Jianzhuang Liu, Xiaodan Liang, Wei Ke
Main Conference Track
Saliency-Aware Neural Architecture Search Ramtin Hosseini, Pengtao Xie
Main Conference Track
VaiPhy: a Variational Inference Based Algorithm for Phylogeny Hazal Koptagel, Oskar Kviman, Harald Melin, Negar Safinianaini, Jens Lagergren
Main Conference Track
A simple but strong baseline for online continual learning: Repeated Augmented Rehearsal Yaqian Zhang, Bernhard Pfahringer, Eibe Frank, Albert Bifet, Nick Jin Sean Lim, Yunzhe Jia
Main Conference Track
You Only Live Once: Single-Life Reinforcement Learning Annie Chen, Archit Sharma, Sergey Levine, Chelsea Finn
Main Conference Track
Compressible-composable NeRF via Rank-residual Decomposition Jiaxiang Tang, Xiaokang Chen, Jingbo Wang, Gang Zeng
Main Conference Track
Data-Efficient Pipeline for Offline Reinforcement Learning with Limited Data Allen Nie, Yannis Flet-Berliac, Deon Jordan, William Steenbergen, Emma Brunskill
Main Conference Track
Hardness in Markov Decision Processes: Theory and Practice Michelangelo Conserva, Paulo Rauber
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Injecting Domain Knowledge from Empirical Interatomic Potentials to Neural Networks for Predicting Material Properties Zeren Shui, Daniel Karls, Mingjian Wen, ilia Nikiforov, Ellad Tadmor, George Karypis
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Learning Modular Simulations for Homogeneous Systems Jayesh Gupta, Sai Vemprala, Ashish Kapoor
Main Conference Track
On Gap-dependent Bounds for Offline Reinforcement Learning Xinqi Wang, Qiwen Cui, Simon S Du
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Semi-Discrete Normalizing Flows through Differentiable Tessellation Ricky T. Q. Chen, Brandon Amos, Maximilian Nickel
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Don't Pour Cereal into Coffee: Differentiable Temporal Logic for Temporal Action Segmentation Ziwei Xu, Yogesh Rawat, Yongkang Wong, Mohan S Kankanhalli, Mubarak Shah
Main Conference Track
Batch-Size Independent Regret Bounds for Combinatorial Semi-Bandits with Probabilistically Triggered Arms or Independent Arms Xutong Liu, Jinhang Zuo, Siwei Wang, Carlee Joe-Wong, John C.S. Lui, Wei Chen
Main Conference Track
Less-forgetting Multi-lingual Fine-tuning Yuren Mao, Yaobo Liang, Nan Duan, Haobo Wang, Kai Wang, Lu Chen, Yunjun Gao
Main Conference Track
Adversarial Attack on Attackers: Post-Process to Mitigate Black-Box Score-Based Query Attacks Sizhe Chen, Zhehao Huang, Qinghua Tao, Yingwen Wu, Cihang Xie, Xiaolin Huang
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Retaining Knowledge for Learning with Dynamic Definition Zichang Liu, Benjamin Coleman, Tianyi Zhang, Anshumali Shrivastava
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HUMANISE: Language-conditioned Human Motion Generation in 3D Scenes Zan Wang, Yixin Chen, Tengyu Liu, Yixin Zhu, Wei Liang, Siyuan Huang
Main Conference Track
Keypoint-Guided Optimal Transport with Applications in Heterogeneous Domain Adaptation Xiang Gu, Yucheng Yang, Wei Zeng, Jian Sun, Zongben Xu
Main Conference Track
Sequence-to-Set Generative Models Longtao Tang, Ying Zhou, Yu Yang
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Near-Optimal Multi-Agent Learning for Safe Coverage Control Manish Prajapat, Matteo Turchetta, Melanie Zeilinger, Andreas Krause
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Network change point localisation under local differential privacy Mengchu Li, Tom Berrett, Yi Yu
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Independence Testing for Bounded Degree Bayesian Networks Arnab Bhattacharyya, Clément L Canonne, Qiping Yang
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Beyond spectral gap: the role of the topology in decentralized learning Thijs Vogels, Hadrien Hendrikx, Martin Jaggi
Main Conference Track
GriddlyJS: A Web IDE for Reinforcement Learning Christopher Bamford, Minqi Jiang, Mikayel Samvelyan, Tim Rocktäschel
Datasets and Benchmarks Track
Periodic Graph Transformers for Crystal Material Property Prediction Keqiang Yan, Yi Liu, Yuchao Lin, Shuiwang Ji
Main Conference Track
Decentralized, Communication- and Coordination-free Learning in Structured Matching Markets Chinmay Maheshwari, Shankar Sastry, Eric Mazumdar
Main Conference Track
Improving GANs with A Dynamic Discriminator Ceyuan Yang, Yujun Shen, Yinghao Xu, Deli Zhao, Bo Dai, Bolei Zhou
Main Conference Track
Deliberated Domain Bridging for Domain Adaptive Semantic Segmentation Lin Chen, Zhixiang Wei, Xin Jin, Huaian Chen, Miao Zheng, Kai Chen, Yi Jin
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Learning to Share in Networked Multi-Agent Reinforcement Learning Yuxuan Yi, Ge Li, Yaowei Wang, Zongqing Lu
Main Conference Track
Scalable and Efficient Non-adaptive Deterministic Group Testing Dariusz Kowalski, Dominik Pajak
Main Conference Track
Structure-Preserving 3D Garment Modeling with Neural Sewing Machines Xipeng Chen, Guangrun Wang, Dizhong Zhu, Xiaodan Liang, Philip Torr, Liang Lin
Main Conference Track
Rethinking Variational Inference for Probabilistic Programs with Stochastic Support Tim Reichelt, Luke Ong, Thomas Rainforth
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Variance Reduced ProxSkip: Algorithm, Theory and Application to Federated Learning Grigory Malinovsky, Kai Yi, Peter Richtarik
Main Conference Track
DreamShard: Generalizable Embedding Table Placement for Recommender Systems Daochen Zha, Louis Feng, Qiaoyu Tan, Zirui Liu, Kwei-Herng Lai, Bhargav Bhushanam, Yuandong Tian, Arun Kejariwal, Xia Hu
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Order-Invariant Cardinality Estimators Are Differentially Private Charlie Dickens, Justin Thaler, Daniel Ting
Main Conference Track
NeuForm: Adaptive Overfitting for Neural Shape Editing Connor Lin, Niloy Mitra, Gordon Wetzstein, Leonidas Guibas, Paul Guerrero
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Inductive Logical Query Answering in Knowledge Graphs Michael Galkin, Zhaocheng Zhu, Hongyu Ren, Jian Tang
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Drawing out of Distribution with Neuro-Symbolic Generative Models Yichao Liang, Josh Tenenbaum, Tuan Anh Le, Siddharth N
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Unsupervised Object Representation Learning using Translation and Rotation Group Equivariant VAE Alireza Nasiri, Tristan Bepler
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PointTAD: Multi-Label Temporal Action Detection with Learnable Query Points Jing Tan, Xiaotong Zhao, Xintian Shi, Bin Kang, Limin Wang
Main Conference Track
Unpacking Reward Shaping: Understanding the Benefits of Reward Engineering on Sample Complexity Abhishek Gupta, Aldo Pacchiano, Yuexiang Zhai, Sham Kakade, Sergey Levine
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LASSIE: Learning Articulated Shapes from Sparse Image Ensemble via 3D Part Discovery Chun-Han Yao, Wei-Chih Hung, Yuanzhen Li, Michael Rubinstein, Ming-Hsuan Yang, Varun Jampani
Main Conference Track
Retrieval-Augmented Diffusion Models Andreas Blattmann, Robin Rombach, Kaan Oktay, Jonas Müller, Björn Ommer
Main Conference Track
Logical Credal Networks Radu Marinescu, Haifeng Qian, Alexander G. Gray, Debarun Bhattacharjya, Francisco Barahona, Tian Gao, Ryan Riegel, Pravinda Sahu
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Neural Set Function Extensions: Learning with Discrete Functions in High Dimensions Nikolaos Karalias, Joshua W. Robinson, Andreas Loukas, Stefanie Jegelka
Main Conference Track
Minimax-Optimal Multi-Agent RL in Markov Games With a Generative Model Gen Li, Yuejie Chi, Yuting Wei, Yuxin Chen
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Bi-directional Weakly Supervised Knowledge Distillation for Whole Slide Image Classification Linhao Qu, xiaoyuan luo, Manning Wang, Zhijian Song
Main Conference Track
Private and Communication-Efficient Algorithms for Entropy Estimation Gecia Bravo-Hermsdorff, Róbert Busa-Fekete, Mohammad Ghavamzadeh, Andres Munoz Medina, Umar Syed
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PKD: General Distillation Framework for Object Detectors via Pearson Correlation Coefficient Weihan Cao, Yifan Zhang, Jianfei Gao, Anda Cheng, Ke Cheng, Jian Cheng
Main Conference Track
Off-Team Learning Brandon Cui, Hengyuan Hu, Andrei Lupu, Samuel Sokota, Jakob Foerster
Main Conference Track
NUWA-Infinity: Autoregressive over Autoregressive Generation for Infinite Visual Synthesis Jian Liang, Chenfei Wu, Xiaowei Hu, Zhe Gan, Jianfeng Wang, Lijuan Wang, Zicheng Liu, Yuejian Fang, Nan Duan
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SoftPatch: Unsupervised Anomaly Detection with Noisy Data Xi Jiang, Jianlin Liu, Jinbao Wang, Qiang Nie, Kai WU, Yong Liu, Chengjie Wang, Feng Zheng
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Stability Analysis and Generalization Bounds of Adversarial Training Jiancong Xiao, Yanbo Fan, Ruoyu Sun, Jue Wang, Zhi-Quan Luo
Main Conference Track
LasUIE: Unifying Information Extraction with Latent Adaptive Structure-aware Generative Language Model Hao Fei, Shengqiong Wu, Jingye Li, Bobo Li, Fei Li, Libo Qin, Meishan Zhang, Min Zhang, Tat-Seng Chua
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STaR: Bootstrapping Reasoning With Reasoning Eric Zelikman, Yuhuai Wu, Jesse Mu, Noah Goodman
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TPU-KNN: K Nearest Neighbor Search at Peak FLOP/s Felix Chern, Blake Hechtman, Andy Davis, Ruiqi Guo, David Majnemer, Sanjiv Kumar
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Efficient Meta Reinforcement Learning for Preference-based Fast Adaptation Zhizhou Ren, Anji Liu, Yitao Liang, Jian Peng, Jianzhu Ma
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Weakly Supervised Representation Learning with Sparse Perturbations Kartik Ahuja, Jason S Hartford, Yoshua Bengio
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A Multi-Resolution Framework for U-Nets with Applications to Hierarchical VAEs Fabian Falck, Christopher K. I. Williams, Dominic Danks, George Deligiannidis, Christopher Yau, Chris C Holmes, Arnaud Doucet, Matthew Willetts
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Watermarking for Out-of-distribution Detection Qizhou Wang, Feng Liu, Yonggang Zhang, Jing Zhang, Chen Gong, Tongliang Liu, Bo Han
Main Conference Track
K-LITE: Learning Transferable Visual Models with External Knowledge Sheng Shen, Chunyuan Li, Xiaowei Hu, Yujia Xie, Jianwei Yang, Pengchuan Zhang, Zhe Gan, Lijuan Wang, Lu Yuan, Ce Liu, Kurt Keutzer, Trevor Darrell, Anna Rohrbach, Jianfeng Gao
Main Conference Track
VeriDark: A Large-Scale Benchmark for Authorship Verification on the Dark Web Andrei Manolache, Florin Brad, Antonio Barbalau, Radu Tudor Ionescu, Marius Popescu
Datasets and Benchmarks Track
EHRSQL: A Practical Text-to-SQL Benchmark for Electronic Health Records Gyubok Lee, Hyeonji Hwang, Seongsu Bae, Yeonsu Kwon, Woncheol Shin, Seongjun Yang, Minjoon Seo, Jong-Yeup Kim, Edward Choi
Datasets and Benchmarks Track
Where do Models go Wrong? Parameter-Space Saliency Maps for Explainability Roman Levin, Manli Shu, Eitan Borgnia, Furong Huang, Micah Goldblum, Tom Goldstein
Main Conference Track
Using Embeddings for Causal Estimation of Peer Influence in Social Networks Irina Cristali, Victor Veitch
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Collaborative Learning by Detecting Collaboration Partners Shu Ding, Wei Wang
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Linear Label Ranking with Bounded Noise Dimitris Fotakis, Alkis Kalavasis, Vasilis Kontonis, Christos Tzamos
Main Conference Track
Quo Vadis: Is Trajectory Forecasting the Key Towards Long-Term Multi-Object Tracking? Patrick Dendorfer, Vladimir Yugay, Aljosa Osep, Laura Leal-Taixé
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Wasserstein Iterative Networks for Barycenter Estimation Alexander Korotin, Vage Egiazarian, Lingxiao Li, Evgeny Burnaev
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Identifiability of deep generative models without auxiliary information Bohdan Kivva, Goutham Rajendran, Pradeep K. Ravikumar, Bryon Aragam
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Task Discovery: Finding the Tasks that Neural Networks Generalize on Andrei Atanov, Andrei Filatov, Teresa Yeo, Ajay Sohmshetty, Amir Zamir
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Iron: Private Inference on Transformers Meng Hao, Hongwei Li, Hanxiao Chen, Pengzhi Xing, Guowen Xu, Tianwei Zhang
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On Batch Teaching with Sample Complexity Bounded by VCD Farnam Mansouri, Hans Simon, Adish Singla, Sandra Zilles
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Approaching Quartic Convergence Rates for Quasi-Stochastic Approximation with Application to Gradient-Free Optimization Caio Kalil Lauand, Sean Meyn
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PAC: Assisted Value Factorization with Counterfactual Predictions in Multi-Agent Reinforcement Learning Hanhan Zhou, Tian Lan, Vaneet Aggarwal
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Translation-equivariant Representation in Recurrent Networks with a Continuous Manifold of Attractors Wenhao Zhang, Ying Nian Wu, Si Wu
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OpenXAI: Towards a Transparent Evaluation of Model Explanations Chirag Agarwal, Satyapriya Krishna, Eshika Saxena, Martin Pawelczyk, Nari Johnson, Isha Puri, Marinka Zitnik, Himabindu Lakkaraju
Datasets and Benchmarks Track
Better Best of Both Worlds Bounds for Bandits with Switching Costs Idan Amir, Guy Azov, Tomer Koren, Roi Livni
Main Conference Track
Uncertainty-Aware Hierarchical Refinement for Incremental Implicitly-Refined Classification Jian Yang, Kai Zhu, Kecheng Zheng, Yang Cao
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The Hessian Screening Rule Johan Larsson, Jonas Wallin
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Sharp Analysis of Stochastic Optimization under Global Kurdyka-Lojasiewicz Inequality Ilyas Fatkhullin, Jalal Etesami, Niao He, Negar Kiyavash
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Plan To Predict: Learning an Uncertainty-Foreseeing Model For Model-Based Reinforcement Learning Zifan Wu, Chao Yu, Chen Chen, Jianye Hao, Hankz Hankui Zhuo
Main Conference Track
Co-Modality Graph Contrastive Learning for Imbalanced Node Classification Yiyue Qian, Chunhui Zhang, Yiming Zhang, Qianlong Wen, Yanfang Ye, Chuxu Zhang
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Efficiency Ordering of Stochastic Gradient Descent Jie Hu, Vishwaraj Doshi, Do-Young Eun
Main Conference Track
Muffliato: Peer-to-Peer Privacy Amplification for Decentralized Optimization and Averaging Edwige Cyffers, Mathieu Even, Aurélien Bellet, Laurent Massoulié
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Mining Multi-Label Samples from Single Positive Labels Youngin Cho, Daejin Kim, MOHAMMAD AZAM KHAN, Jaegul Choo
Main Conference Track
Sequential Information Design: Learning to Persuade in the Dark Martino Bernasconi, Matteo Castiglioni, Alberto Marchesi, Nicola Gatti, Francesco Trovò
Main Conference Track
AutoML Two-Sample Test Jonas M. Kübler, Vincent Stimper, Simon Buchholz, Krikamol Muandet, Bernhard Schölkopf
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Cross-Linked Unified Embedding for cross-modality representation learning Xinming Tu, Zhi-Jie Cao, xia chenrui, Sara Mostafavi, Ge Gao
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Learning Individualized Treatment Rules with Many Treatments: A Supervised Clustering Approach Using Adaptive Fusion Haixu Ma, Donglin Zeng, Yufeng Liu
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Robust Generalized Method of Moments: A Finite Sample Viewpoint Dhruv Rohatgi, Vasilis Syrgkanis
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$k$-Sliced Mutual Information: A Quantitative Study of Scalability with Dimension Ziv Goldfeld, Kristjan Greenewald, Theshani Nuradha, Galen Reeves
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What's the Harm? Sharp Bounds on the Fraction Negatively Affected by Treatment Nathan Kallus
Main Conference Track
Bessel Equivariant Networks for Inversion of Transmission Effects in Multi-Mode Optical Fibres Joshua Mitton, Simon Mekhail, Miles Padgett, Daniele Faccio, Marco Aversa, Roderick Murray-Smith
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Training Subset Selection for Weak Supervision Hunter Lang, Aravindan Vijayaraghavan, David Sontag
Main Conference Track
Expansion and Shrinkage of Localization for Weakly-Supervised Semantic Segmentation Jinlong Li, Zequn Jie, Xu Wang, Xiaolin Wei, Lin Ma
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No Free Lunch from Deep Learning in Neuroscience: A Case Study through Models of the Entorhinal-Hippocampal Circuit Rylan Schaeffer, Mikail Khona, Ila Fiete
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On the Importance of Gradient Norm in PAC-Bayesian Bounds Itai Gat, Yossi Adi, Alex Schwing, Tamir Hazan
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RAMBO-RL: Robust Adversarial Model-Based Offline Reinforcement Learning Marc Rigter, Bruno Lacerda, Nick Hawes
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Learning NP-Hard Multi-Agent Assignment Planning using GNN: Inference on a Random Graph and Provable Auction-Fitted Q-learning HYUNWOOK KANG, Taehwan Kwon, Jinkyoo Park, James R. Morrison
Main Conference Track
Improved techniques for deterministic l2 robustness Sahil Singla, Soheil Feizi
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Normalizing Flows for Knockoff-free Controlled Feature Selection Derek Hansen, Brian Manzo, Jeffrey Regier
Main Conference Track
ReFactor GNNs: Revisiting Factorisation-based Models from a Message-Passing Perspective Yihong Chen, Pushkar Mishra, Luca Franceschi, Pasquale Minervini, Pontus Lars Erik Saito Stenetorp, Sebastian Riedel
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Efficient Architecture Search for Diverse Tasks Junhong Shen, Misha Khodak, Ameet Talwalkar
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Beyond Not-Forgetting: Continual Learning with Backward Knowledge Transfer Sen Lin, Li Yang, Deliang Fan, Junshan Zhang
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Inherently Explainable Reinforcement Learning in Natural Language Xiangyu Peng, Mark Riedl, Prithviraj Ammanabrolu
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Conditional Independence Testing with Heteroskedastic Data and Applications to Causal Discovery Wiebke Günther, Urmi Ninad, Jonas Wahl, Jakob Runge
Main Conference Track
On Reinforcement Learning and Distribution Matching for Fine-Tuning Language Models with no Catastrophic Forgetting Tomasz Korbak, Hady Elsahar, Germán Kruszewski, Marc Dymetman
Main Conference Track
Ask4Help: Learning to Leverage an Expert for Embodied Tasks Kunal Pratap Singh, Luca Weihs, Alvaro Herrasti, Jonghyun Choi, Aniruddha Kembhavi, Roozbeh Mottaghi
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Human-AI Collaborative Bayesian Optimisation Arun Kumar A V, Santu Rana, Alistair Shilton, Svetha Venkatesh
Main Conference Track
Robust Learning against Relational Adversaries Yizhen Wang, Mohannad Alhanahnah, Xiaozhu Meng, Ke Wang, Mihai Christodorescu, Somesh Jha
Main Conference Track
Active Bayesian Causal Inference Christian Toth, Lars Lorch, Christian Knoll, Andreas Krause, Franz Pernkopf, Robert Peharz, Julius von Kügelgen
Main Conference Track
Understanding and Improving Robustness of Vision Transformers through Patch-based Negative Augmentation Yao Qin, Chiyuan Zhang, Ting Chen, Balaji Lakshminarayanan, Alex Beutel, Xuezhi Wang
Main Conference Track
LogiGAN: Learning Logical Reasoning via Adversarial Pre-training Xinyu Pi, Wanjun Zhong, Yan Gao, Nan Duan, Jian-Guang Lou
Main Conference Track
Revisiting Non-Parametric Matching Cost Volumes for Robust and Generalizable Stereo Matching Kelvin Cheng, Tianfu Wu, Christopher Healey
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On the Interpretability of Regularisation for Neural Networks Through Model Gradient Similarity Vincent Szolnoky, Viktor Andersson, Balazs Kulcsar, Rebecka Jörnsten
Main Conference Track
Controllable 3D Face Synthesis with Conditional Generative Occupancy Fields Keqiang Sun, Shangzhe Wu, Zhaoyang Huang, Ning Zhang, Quan Wang, Hongsheng Li
Main Conference Track
FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness Tri Dao, Dan Fu, Stefano Ermon, Atri Rudra, Christopher Ré
Main Conference Track
Locally Hierarchical Auto-Regressive Modeling for Image Generation Tackgeun You, Saehoon Kim, Chiheon Kim, Doyup Lee, Bohyung Han
Main Conference Track
Learning Enhanced Representation for Tabular Data via Neighborhood Propagation Kounianhua Du, Weinan Zhang, Ruiwen Zhou, Yangkun Wang, Xilong Zhao, Jiarui Jin, Quan Gan, Zheng Zhang, David P Wipf
Main Conference Track
On global convergence of ResNets: From finite to infinite width using linear parameterization Raphaël Barboni, Gabriel Peyré, Francois-Xavier Vialard
Main Conference Track
Spherization Layer: Representation Using Only Angles Hoyong Kim, kangil kim
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On the Identifiability of Nonlinear ICA: Sparsity and Beyond Yujia Zheng, Ignavier Ng, Kun Zhang
Main Conference Track
Self-Supervised Visual Representation Learning with Semantic Grouping Xin Wen, Bingchen Zhao, Anlin Zheng, Xiangyu Zhang, Xiaojuan Qi
Main Conference Track
Optimistic Mirror Descent Either Converges to Nash or to Strong Coarse Correlated Equilibria in Bimatrix Games Ioannis Anagnostides, Gabriele Farina, Ioannis Panageas, Tuomas Sandholm
Main Conference Track
Discovered Policy Optimisation Chris Lu, Jakub Kuba, Alistair Letcher, Luke Metz, Christian Schroeder de Witt, Jakob Foerster
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Robust Testing in High-Dimensional Sparse Models Anand Jerry George, Clément L Canonne
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Learning Consistency-Aware Unsigned Distance Functions Progressively from Raw Point Clouds Junsheng Zhou, Baorui Ma, Yu-Shen Liu, Yi Fang, Zhizhong Han
Main Conference Track
Understanding Square Loss in Training Overparametrized Neural Network Classifiers Tianyang Hu, Jun WANG, Wenjia Wang, Zhenguo Li
Main Conference Track
Multi-Agent Reinforcement Learning is a Sequence Modeling Problem Muning Wen, Jakub Kuba, Runji Lin, Weinan Zhang, Ying Wen, Jun Wang, Yaodong Yang
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Non-stationary Bandits with Knapsacks Shang Liu, Jiashuo Jiang, Xiaocheng Li
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Fast Bayesian Inference with Batch Bayesian Quadrature via Kernel Recombination Masaki Adachi, Satoshi Hayakawa, Martin Jørgensen, Harald Oberhauser, Michael A Osborne
Main Conference Track
Are Two Heads the Same as One? Identifying Disparate Treatment in Fair Neural Networks Michael Lohaus, Matthäus Kleindessner, Krishnaram Kenthapadi, Francesco Locatello, Chris Russell
Main Conference Track
Provable Generalization of Overparameterized Meta-learning Trained with SGD Yu Huang, Yingbin Liang, Longbo Huang
Main Conference Track
When Do Flat Minima Optimizers Work? Jean Kaddour, Linqing Liu, Ricardo Silva, Matt J Kusner
Main Conference Track
Fast Instrument Learning with Faster Rates Ziyu Wang, Yuhao Zhou, Jun Zhu
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Sparse Gaussian Process Hyperparameters: Optimize or Integrate? Vidhi Lalchand, Wessel Bruinsma, David Burt, Carl Edward Rasmussen
Main Conference Track
HierSpeech: Bridging the Gap between Text and Speech by Hierarchical Variational Inference using Self-supervised Representations for Speech Synthesis Sang-Hoon Lee, Seung-Bin Kim, Ji-Hyun Lee, Eunwoo Song, Min-Jae Hwang, Seong-Whan Lee
Main Conference Track
Sharing Knowledge for Meta-learning with Feature Descriptions Tomoharu Iwata, Atsutoshi Kumagai
Main Conference Track
A Variant of Anderson Mixing with Minimal Memory Size Fuchao Wei, Chenglong Bao, Yang Liu, Guangwen Yang
Main Conference Track
AdaptFormer: Adapting Vision Transformers for Scalable Visual Recognition Shoufa Chen, Chongjian GE, Zhan Tong, Jiangliu Wang, Yibing Song, Jue Wang, Ping Luo
Main Conference Track
Symmetry Teleportation for Accelerated Optimization Bo Zhao, Nima Dehmamy, Robin Walters, Rose Yu
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Wasserstein Logistic Regression with Mixed Features Aras Selvi, Mohammad Reza Belbasi, Martin Haugh, Wolfram Wiesemann
Main Conference Track
TaiSu: A 166M Large-scale High-Quality Dataset for Chinese Vision-Language Pre-training Yulong Liu, Guibo Zhu, Bin Zhu, Qi Song, Guojing Ge, Haoran Chen, GuanHui Qiao, Ru Peng, Lingxiang Wu, Jinqiao Wang
Datasets and Benchmarks Track
Robust Bayesian Regression via Hard Thresholding Zheyi Fan, Zhaohui Li, Qingpei Hu
Main Conference Track
Trajectory Inference via Mean-field Langevin in Path Space Lénaïc Chizat, Stephen Zhang, Matthieu Heitz, Geoffrey Schiebinger
Main Conference Track
SwinTrack: A Simple and Strong Baseline for Transformer Tracking Liting Lin, Heng Fan, Zhipeng Zhang, Yong Xu, Haibin Ling
Main Conference Track
Unknown-Aware Domain Adversarial Learning for Open-Set Domain Adaptation JoonHo Jang, Byeonghu Na, Dong Hyeok Shin, Mingi Ji, Kyungwoo Song, Il-chul Moon
Main Conference Track
Learning Chaotic Dynamics in Dissipative Systems Zongyi Li, Miguel Liu-Schiaffini, Nikola Kovachki, Kamyar Azizzadenesheli, Burigede Liu, Kaushik Bhattacharya, Andrew Stuart, Anima Anandkumar
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Poisson Flow Generative Models Yilun Xu, Ziming Liu, Max Tegmark, Tommi Jaakkola
Main Conference Track
Bounding and Approximating Intersectional Fairness through Marginal Fairness Mathieu Molina, Patrick Loiseau
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Semi-infinitely Constrained Markov Decision Processes Liangyu Zhang, Yang Peng, Wenhao Yang, Zhihua Zhang
Main Conference Track
Latent Planning via Expansive Tree Search Robert Gieselmann, Florian T. Pokorny
Main Conference Track
Invertible Monotone Operators for Normalizing Flows Byeongkeun Ahn, Chiyoon Kim, Youngjoon Hong, Hyunwoo J Kim
Main Conference Track
Dynamic Sparse Network for Time Series Classification: Learning What to “See” Qiao Xiao, Boqian Wu, Yu Zhang, Shiwei Liu, Mykola Pechenizkiy, Elena Mocanu, Decebal Constantin Mocanu
Main Conference Track
Learning to Sample and Aggregate: Few-shot Reasoning over Temporal Knowledge Graphs Ruijie Wang, Zheng Li, Dachun Sun, Shengzhong Liu, Jinning Li, Bing Yin, Tarek Abdelzaher
Main Conference Track
Evaluating Robustness to Dataset Shift via Parametric Robustness Sets Nikolaj Thams, Michael Oberst, David Sontag
Main Conference Track
CogView2: Faster and Better Text-to-Image Generation via Hierarchical Transformers Ming Ding, Wendi Zheng, Wenyi Hong, Jie Tang
Main Conference Track
Recursive Reasoning in Minimax Games: A Level $k$ Gradient Play Method Zichu Liu, Lacra Pavel
Main Conference Track
When to Ask for Help: Proactive Interventions in Autonomous Reinforcement Learning Annie Xie, Fahim Tajwar, Archit Sharma, Chelsea Finn
Main Conference Track
Reinforcement Learning with Neural Radiance Fields Danny Driess, Ingmar Schubert, Pete Florence, Yunzhu Li, Marc Toussaint
Main Conference Track
Function Classes for Identifiable Nonlinear Independent Component Analysis Simon Buchholz, Michel Besserve, Bernhard Schölkopf
Main Conference Track
Self-supervised Heterogeneous Graph Pre-training Based on Structural Clustering Yaming Yang, Ziyu Guan, Zhe Wang, Wei Zhao, Cai Xu, Weigang Lu, Jianbin Huang
Main Conference Track
Learning Audio-Visual Dynamics Using Scene Graphs for Audio Source Separation Moitreya Chatterjee, Narendra Ahuja, Anoop Cherian
Main Conference Track
On the Sample Complexity of Stabilizing LTI Systems on a Single Trajectory Yang Hu, Adam Wierman, Guannan Qu
Main Conference Track
coVariance Neural Networks Saurabh Sihag, Gonzalo Mateos, Corey McMillan, Alejandro Ribeiro
Main Conference Track
Taming Fat-Tailed (“Heavier-Tailed” with Potentially Infinite Variance) Noise in Federated Learning Haibo Yang, Peiwen Qiu, Jia Liu
Main Conference Track
Exploring Figure-Ground Assignment Mechanism in Perceptual Organization Wei Zhai, Yang Cao, Jing Zhang, Zheng-Jun Zha
Main Conference Track
Two-Stream Network for Sign Language Recognition and Translation Yutong Chen, Ronglai Zuo, Fangyun Wei, Yu Wu, Shujie LIU, Brian Mak
Main Conference Track
VisFIS: Visual Feature Importance Supervision with Right-for-the-Right-Reason Objectives Zhuofan Ying, Peter Hase, Mohit Bansal
Main Conference Track
Operative dimensions in unconstrained connectivity of recurrent neural networks Renate Krause, Matthew Cook, Sepp Kollmorgen, Valerio Mante, Giacomo Indiveri
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Batch size-invariance for policy optimization Jacob Hilton, Karl Cobbe, John Schulman
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Inference and Sampling for Archimax Copulas Yuting Ng, Ali Hasan, Vahid Tarokh
Main Conference Track
Neural Shape Deformation Priors Jiapeng Tang, Lev Markhasin, Bi Wang, Justus Thies, Matthias Niessner
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The Curse of Unrolling: Rate of Differentiating Through Optimization Damien Scieur, Gauthier Gidel, Quentin Bertrand, Fabian Pedregosa
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A Deep Learning Dataloader with Shared Data Preparation jian xie, Jingwei Xu, Guochang Wang, Yuan Yao, Zenan Li, Chun Cao, Hanghang Tong
Main Conference Track
Learning Physics Constrained Dynamics Using Autoencoders Tsung-Yen Yang, Justinian P. Rosca, Karthik Narasimhan, Peter J Ramadge
Main Conference Track
Variational Model Perturbation for Source-Free Domain Adaptation Mengmeng Jing, Xiantong Zhen, Jingjing Li, Cees Snoek
Main Conference Track
On the non-universality of deep learning: quantifying the cost of symmetry Emmanuel Abbe, Enric Boix-Adsera
Main Conference Track
Sharper Convergence Guarantees for Asynchronous SGD for Distributed and Federated Learning Anastasiia Koloskova, Sebastian U Stich, Martin Jaggi
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A Unified Framework for Alternating Offline Model Training and Policy Learning Shentao Yang, Shujian Zhang, Yihao Feng, Mingyuan Zhou
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Adjoint-aided inference of Gaussian process driven differential equations Paterne GAHUNGU, Christopher Lanyon, Mauricio A Álvarez, Engineer Bainomugisha, Michael T Smith, Richard Wilkinson
Main Conference Track
BOME! Bilevel Optimization Made Easy: A Simple First-Order Approach Bo Liu, Mao Ye, Stephen Wright, Peter Stone, Qiang Liu
Main Conference Track
Mirror Descent with Relative Smoothness in Measure Spaces, with application to Sinkhorn and EM Pierre-Cyril Aubin-Frankowski, Anna Korba, Flavien Léger
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Peer Prediction for Learning Agents Shi Feng, Fang-Yi Yu, Yiling Chen
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Visual Clues: Bridging Vision and Language Foundations for Image Paragraph Captioning Yujia Xie, Luowei Zhou, Xiyang Dai, Lu Yuan, Nguyen Bach, Ce Liu, Michael Zeng
Main Conference Track
APT-36K: A Large-scale Benchmark for Animal Pose Estimation and Tracking Yuxiang Yang, Junjie Yang, Yufei Xu, Jing Zhang, Long Lan, Dacheng Tao
Datasets and Benchmarks Track
ShuffleMixer: An Efficient ConvNet for Image Super-Resolution Long Sun, Jinshan Pan, Jinhui Tang
Main Conference Track
Neural Topological Ordering for Computation Graphs Mukul Gagrani, Corrado Rainone, Yang Yang, Harris Teague, Wonseok Jeon, Roberto Bondesan, Herke van Hoof, Christopher Lott, Weiliang Zeng, Piero Zappi
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Probable Domain Generalization via Quantile Risk Minimization Cian Eastwood, Alexander Robey, Shashank Singh, Julius von Kügelgen, Hamed Hassani, George J. Pappas, Bernhard Schölkopf
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Locating and Editing Factual Associations in GPT Kevin Meng, David Bau, Alex Andonian, Yonatan Belinkov
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S-PIFu: Integrating Parametric Human Models with PIFu for Single-view Clothed Human Reconstruction Kennard Chan, Guosheng Lin, Haiyu Zhao, Weisi Lin
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A composable machine-learning approach for steady-state simulations on high-resolution grids Rishikesh Ranade, Chris Hill, Lalit Ghule, Jay Pathak
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Outlier Suppression: Pushing the Limit of Low-bit Transformer Language Models Xiuying Wei, Yunchen Zhang, Xiangguo Zhang, Ruihao Gong, Shanghang Zhang, Qi Zhang, Fengwei Yu, Xianglong Liu
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A Single-timescale Analysis for Stochastic Approximation with Multiple Coupled Sequences Han Shen, Tianyi Chen
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Bayesian Risk Markov Decision Processes Yifan Lin, Yuxuan Ren, Enlu Zhou
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All Politics is Local: Redistricting via Local Fairness Shao-Heng Ko, Erin Taylor, Pankaj Agarwal, Kamesh Munagala
Main Conference Track
Confident Adaptive Language Modeling Tal Schuster, Adam Fisch, Jai Gupta, Mostafa Dehghani, Dara Bahri, Vinh Tran, Yi Tay, Donald Metzler
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Submodular Maximization in Clean Linear Time Wenxin Li, Moran Feldman, Ehsan Kazemi, Amin Karbasi
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Parameters or Privacy: A Provable Tradeoff Between Overparameterization and Membership Inference Jasper Tan, Blake Mason, Hamid Javadi, Richard Baraniuk
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EF-BV: A Unified Theory of Error Feedback and Variance Reduction Mechanisms for Biased and Unbiased Compression in Distributed Optimization Laurent Condat, Kai Yi, Peter Richtarik
Main Conference Track
DataMUX: Data Multiplexing for Neural Networks Vishvak Murahari, Carlos Jimenez, Runzhe Yang, Karthik Narasimhan
Main Conference Track
Biologically-plausible backpropagation through arbitrary timespans via local neuromodulators Yuhan Helena Liu, Stephen Smith, Stefan Mihalas, Eric Shea-Brown, Uygar Sümbül
Main Conference Track
Revisiting Realistic Test-Time Training: Sequential Inference and Adaptation by Anchored Clustering Yongyi Su, Xun Xu, Kui Jia
Main Conference Track
Label Noise in Adversarial Training: A Novel Perspective to Study Robust Overfitting Chengyu Dong, Liyuan Liu, Jingbo Shang
Main Conference Track
Active Labeling: Streaming Stochastic Gradients Vivien Cabannes, Francis R. Bach, Vianney Perchet, Alessandro Rudi
Main Conference Track
CEBaB: Estimating the Causal Effects of Real-World Concepts on NLP Model Behavior Eldar D Abraham, Karel D'Oosterlinck, Amir Feder, Yair Gat, Atticus Geiger, Christopher Potts, Roi Reichart, Zhengxuan Wu
Main Conference Track
TOIST: Task Oriented Instance Segmentation Transformer with Noun-Pronoun Distillation Pengfei Li, Beiwen Tian, Yongliang Shi, Xiaoxue Chen, Hao Zhao, Guyue Zhou, Ya-Qin Zhang
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Mind the Gap: Understanding the Modality Gap in Multi-modal Contrastive Representation Learning Victor Weixin Liang, Yuhui Zhang, Yongchan Kwon, Serena Yeung, James Y Zou
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$\alpha$-ReQ : Assessing Representation Quality in Self-Supervised Learning by measuring eigenspectrum decay Kumar K Agrawal, Arnab Kumar Mondal, Arna Ghosh, Blake Richards
Main Conference Track
When Combinatorial Thompson Sampling meets Approximation Regret Pierre Perrault
Main Conference Track
Pruning has a disparate impact on model accuracy Cuong Tran, Ferdinando Fioretto, Jung-Eun Kim, Rakshit Naidu
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Sequence Model Imitation Learning with Unobserved Contexts Gokul Swamy, Sanjiban Choudhury, J. A. Bagnell, Steven Z. Wu
Main Conference Track
Tikhonov Regularization is Optimal Transport Robust under Martingale Constraints Jiajin Li, Sirui Lin, Jose Blanchet, Viet Anh Nguyen
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Policy Optimization with Linear Temporal Logic Constraints Cameron Voloshin, Hoang Le, Swarat Chaudhuri, Yisong Yue
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Merging Models with Fisher-Weighted Averaging Michael S Matena, Colin A Raffel
Main Conference Track
Learning to Generate Inversion-Resistant Model Explanations Hoyong Jeong, Suyoung Lee, Sung Ju Hwang, Sooel Son
Main Conference Track
Unsupervised Multi-View Object Segmentation Using Radiance Field Propagation Xinhang Liu, Jiaben Chen, Huai Yu, Yu-Wing Tai, Chi-Keung Tang
Main Conference Track
Beyond Mahalanobis Distance for Textual OOD Detection Pierre Colombo, Eduardo Dadalto, Guillaume Staerman, Nathan Noiry, Pablo Piantanida
Main Conference Track
FasterRisk: Fast and Accurate Interpretable Risk Scores Jiachang Liu, Chudi Zhong, Boxuan Li, Margo Seltzer, Cynthia Rudin
Main Conference Track
Graph Learning Assisted Multi-Objective Integer Programming Yaoxin Wu, Wen Song, Zhiguang Cao, Jie Zhang, Abhishek Gupta, Mingyan Lin
Main Conference Track
Revisiting Sliced Wasserstein on Images: From Vectorization to Convolution Khai Nguyen, Nhat Ho
Main Conference Track
SignRFF: Sign Random Fourier Features Xiaoyun Li, Ping Li
Main Conference Track
The Role of Baselines in Policy Gradient Optimization Jincheng Mei, Wesley Chung, Valentin Thomas, Bo Dai, Csaba Szepesvari, Dale Schuurmans
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A Rotated Hyperbolic Wrapped Normal Distribution for Hierarchical Representation Learning Seunghyuk Cho, Juyong Lee, Jaesik Park, Dongwoo Kim
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Private Graph All-Pairwise-Shortest-Path Distance Release with Improved Error Rate Chenglin Fan, Ping Li, Xiaoyun Li
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Multi-Fidelity Best-Arm Identification Riccardo Poiani, Alberto Maria Metelli, Marcello Restelli
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SemiFL: Semi-Supervised Federated Learning for Unlabeled Clients with Alternate Training Enmao Diao, Jie Ding, Vahid Tarokh
Main Conference Track
RankFeat: Rank-1 Feature Removal for Out-of-distribution Detection Yue Song, Nicu Sebe, Wei Wang
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Jump Self-attention: Capturing High-order Statistics in Transformers Haoyi Zhou, Siyang Xiao, Shanghang Zhang, Jieqi Peng, Shuai Zhang, Jianxin Li
Main Conference Track
Learning Infinite-Horizon Average-Reward Restless Multi-Action Bandits via Index Awareness GUOJUN XIONG, Shufan Wang, Jian Li
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STNDT: Modeling Neural Population Activity with Spatiotemporal Transformers Trung Le, Eli Shlizerman
Main Conference Track
ProtoVAE: A Trustworthy Self-Explainable Prototypical Variational Model Srishti Gautam, Ahcène Boubekki, Stine Hansen, Suaiba Salahuddin, Robert Jenssen, Marina Höhne, Michael Kampffmeyer
Main Conference Track
If Influence Functions are the Answer, Then What is the Question? Juhan Bae, Nathan Ng, Alston Lo, Marzyeh Ghassemi, Roger B Grosse
Main Conference Track
FACT: Learning Governing Abstractions Behind Integer Sequences Peter Belcak, Ard Kastrati, Flavio Schenker, Roger Wattenhofer
Datasets and Benchmarks Track
SAPipe: Staleness-Aware Pipeline for Data Parallel DNN Training Yangrui Chen, Cong Xie, Meng Ma, Juncheng Gu, Yanghua Peng, Haibin Lin, Chuan Wu, Yibo Zhu
Main Conference Track
Probing Classifiers are Unreliable for Concept Removal and Detection Abhinav Kumar, Chenhao Tan, Amit Sharma
Main Conference Track
SCL-WC: Cross-Slide Contrastive Learning for Weakly-Supervised Whole-Slide Image Classification Xiyue Wang, Jinxi Xiang, Jun Zhang, Sen Yang, Zhongyi Yang, Ming-Hui Wang, Jing Zhang, Wei Yang, Junzhou Huang, Xiao Han
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Reproducibility in Optimization: Theoretical Framework and Limits Kwangjun Ahn, Prateek Jain, Ziwei Ji, Satyen Kale, Praneeth Netrapalli, Gil I Shamir
Main Conference Track
Hierarchical classification at multiple operating points Jack Valmadre
Main Conference Track
Kernel Multimodal Continuous Attention Alexander Moreno, Zhenke Wu, Supriya Nagesh, Walter Dempsey, James M. Rehg
Main Conference Track
VisCo Grids: Surface Reconstruction with Viscosity and Coarea Grids Albert Pumarola, Artsiom Sanakoyeu, Lior Yariv, Ali Thabet, Yaron Lipman
Main Conference Track
Exact Shape Correspondence via 2D graph convolution Barakeel Fanseu Kamhoua, Lin Zhang, Yongqiang Chen, Han Yang, MA Kaili, Bo Han, Bo Li, James Cheng
Main Conference Track
Posterior Matching for Arbitrary Conditioning Ryan Strauss, Junier B Oliva
Main Conference Track
CARD: Classification and Regression Diffusion Models Xizewen Han, Huangjie Zheng, Mingyuan Zhou
Main Conference Track
What Can the Neural Tangent Kernel Tell Us About Adversarial Robustness? Nikolaos Tsilivis, Julia Kempe
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Benefits of Permutation-Equivariance in Auction Mechanisms Tian Qin, Fengxiang He, Dingfeng Shi, Wenbing Huang, Dacheng Tao
Main Conference Track
MoCoDA: Model-based Counterfactual Data Augmentation Silviu Pitis, Elliot Creager, Ajay Mandlekar, Animesh Garg
Main Conference Track
SkinCon: A skin disease dataset densely annotated by domain experts for fine-grained debugging and analysis Roxana Daneshjou, Mert Yuksekgonul, Zhuo Ran Cai, Roberto Novoa, James Y Zou
Datasets and Benchmarks Track
A permutation-free kernel two-sample test Shubhanshu Shekhar, Ilmun Kim, Aaditya Ramdas
Main Conference Track
Simple Unsupervised Object-Centric Learning for Complex and Naturalistic Videos Gautam Singh, Yi-Fu Wu, Sungjin Ahn
Main Conference Track
Communication-efficient distributed eigenspace estimation with arbitrary node failures Vasileios Charisopoulos, Anil Damle
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On Uncertainty, Tempering, and Data Augmentation in Bayesian Classification Sanyam Kapoor, Wesley J Maddox, Pavel Izmailov, Andrew G Wilson
Main Conference Track
Optimal Binary Classification Beyond Accuracy Shashank Singh, Justin T Khim
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Information-Theoretic GAN Compression with Variational Energy-based Model Minsoo Kang, Hyewon Yoo, Eunhee Kang, Sehwan Ki, Hyong Euk Lee, Bohyung Han
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On Learning and Refutation in Noninteractive Local Differential Privacy Alexander Edmonds, Aleksandar Nikolov, Toniann Pitassi
Main Conference Track
Why So Pessimistic? Estimating Uncertainties for Offline RL through Ensembles, and Why Their Independence Matters Kamyar Ghasemipour, Shixiang (Shane) Gu, Ofir Nachum
Main Conference Track
Private Synthetic Data for Multitask Learning and Marginal Queries Giuseppe Vietri, Cedric Archambeau, Sergul Aydore, William Brown, Michael J. Kearns, Aaron Roth, Ankit Siva, Shuai Tang, Steven Z. Wu
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Sample-Efficient Reinforcement Learning of Partially Observable Markov Games Qinghua Liu, Csaba Szepesvari, Chi Jin
Main Conference Track
Advancing Model Pruning via Bi-level Optimization Yihua Zhang, Yuguang Yao, Parikshit Ram, Pu Zhao, Tianlong Chen, Mingyi Hong, Yanzhi Wang, Sijia Liu
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Optimal Positive Generation via Latent Transformation for Contrastive Learning Yinqi Li, Hong Chang, Bingpeng MA, Shiguang Shan, Xilin Chen
Main Conference Track
MineDojo: Building Open-Ended Embodied Agents with Internet-Scale Knowledge Linxi Fan, Guanzhi Wang, Yunfan Jiang, Ajay Mandlekar, Yuncong Yang, Haoyi Zhu, Andrew Tang, De-An Huang, Yuke Zhu, Anima Anandkumar
Datasets and Benchmarks Track
The price of unfairness in linear bandits with biased feedback Solenne Gaucher, Alexandra Carpentier, Christophe Giraud
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DeepFoids: Adaptive Bio-Inspired Fish Simulation with Deep Reinforcement Learning Yuko Ishiwaka, Xiao Zeng, Shun Ogawa, Donovan Westwater, Tadayuki Tone, Masaki Nakada
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Truncated Matrix Power Iteration for Differentiable DAG Learning Zhen Zhang, Ignavier Ng, Dong Gong, Yuhang Liu, Ehsan Abbasnejad, Mingming Gong, Kun Zhang, Javen Qinfeng Shi
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Learning Debiased Classifier with Biased Committee Nayeong Kim, SEHYUN HWANG, Sungsoo Ahn, Jaesik Park, Suha Kwak
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Modeling the Machine Learning Multiverse Samuel J. Bell, Onno Kampman, Jesse Dodge, Neil D. Lawrence
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Label-Aware Global Consistency for Multi-Label Learning with Single Positive Labels Ming-Kun Xie, Jiahao Xiao, Sheng-Jun Huang
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Unifying Voxel-based Representation with Transformer for 3D Object Detection Yanwei Li, Yilun Chen, Xiaojuan Qi, Zeming Li, Jian Sun, Jiaya Jia
Main Conference Track
UDC: Unified DNAS for Compressible TinyML Models for Neural Processing Units Igor Fedorov, Ramon Matas, Hokchhay Tann, Chuteng Zhou, Matthew Mattina, Paul Whatmough
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Measures of Information Reflect Memorization Patterns Rachit Bansal, Danish Pruthi, Yonatan Belinkov
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Fine-Grained Analysis of Stability and Generalization for Modern Meta Learning Algorithms Jiechao Guan, Yong Liu, Zhiwu Lu
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On Scrambling Phenomena for Randomly Initialized Recurrent Networks Vaggos Chatziafratis, Ioannis Panageas, Clayton Sanford, Stelios Stavroulakis
Main Conference Track
Learning to Branch with Tree MDPs Lara Scavuzzo, Feng Chen, Didier Chetelat, Maxime Gasse, Andrea Lodi, Neil Yorke-Smith, Karen Aardal
Main Conference Track
Neural Sheaf Diffusion: A Topological Perspective on Heterophily and Oversmoothing in GNNs Cristian Bodnar, Francesco Di Giovanni, Benjamin Chamberlain, Pietro Lió, Michael Bronstein
Main Conference Track
pyKT: A Python Library to Benchmark Deep Learning based Knowledge Tracing Models Zitao Liu, Qiongqiong Liu, Jiahao Chen, Shuyan Huang, Jiliang Tang, Weiqi Luo
Datasets and Benchmarks Track
Adversarial Unlearning: Reducing Confidence Along Adversarial Directions Amrith Setlur, Benjamin Eysenbach, Virginia Smith, Sergey Levine
Main Conference Track
How Would The Viewer Feel? Estimating Wellbeing From Video Scenarios Mantas Mazeika, Eric Tang, Andy Zou, Steven Basart, Jun Shern Chan, Dawn Song, David A. Forsyth, Jacob Steinhardt, Dan Hendrycks
Datasets and Benchmarks Track
On Elimination Strategies for Bandit Fixed-Confidence Identification Andrea Tirinzoni, Rémy Degenne
Main Conference Track
When Adversarial Training Meets Vision Transformers: Recipes from Training to Architecture Yichuan Mo, Dongxian Wu, Yifei Wang, Yiwen Guo, Yisen Wang
Main Conference Track
Escaping from the Barren Plateau via Gaussian Initializations in Deep Variational Quantum Circuits Kaining Zhang, Liu Liu, Min-Hsiu Hsieh, Dacheng Tao
Main Conference Track
A sharp NMF result with applications in network modeling Jiashun Jin
Main Conference Track
Decoupling Classifier for Boosting Few-shot Object Detection and Instance Segmentation Bin-Bin Gao, Xiaochen Chen, Zhongyi Huang, Congchong Nie, Jun Liu, Jinxiang Lai, GUANNAN JIANG, Xi Wang, Chengjie Wang
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Private Estimation with Public Data Alex Bie, Gautam Kamath, Vikrant Singhal
Main Conference Track
Pre-activation Distributions Expose Backdoor Neurons Runkai Zheng, Rongjun Tang, Jianze Li, Li Liu
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DaDA: Distortion-aware Domain Adaptation for Unsupervised Semantic Segmentation Sujin Jang, Joohan Na, Dokwan Oh
Main Conference Track
Large-batch Optimization for Dense Visual Predictions: Training Faster R-CNN in 4.2 Minutes Zeyue Xue, Jianming Liang, Guanglu Song, Zhuofan Zong, Liang Chen, Yu Liu, Ping Luo
Main Conference Track
Most Activation Functions Can Win the Lottery Without Excessive Depth Rebekka Burkholz
Main Conference Track
Rapid Model Architecture Adaption for Meta-Learning Yiren Zhao, Xitong Gao, I Shumailov, Nicolo Fusi, Robert Mullins
Main Conference Track
Exploring through Random Curiosity with General Value Functions Aditya Ramesh, Louis Kirsch, Sjoerd van Steenkiste, Jürgen Schmidhuber
Main Conference Track
Optimal Transport-based Identity Matching for Identity-invariant Facial Expression Recognition Daeha Kim, Byung Cheol Song
Main Conference Track
Unsupervised Learning under Latent Label Shift Manley Roberts, Pranav Mani, Saurabh Garg, Zachary Lipton
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SHINE: SubHypergraph Inductive Neural nEtwork Yuan Luo
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Efficient Aggregated Kernel Tests using Incomplete $U$-statistics Antonin Schrab, Ilmun Kim, Benjamin Guedj, Arthur Gretton
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Influencing Long-Term Behavior in Multiagent Reinforcement Learning Dong-Ki Kim, Matthew Riemer, Miao Liu, Jakob Foerster, Michael Everett, Chuangchuang Sun, Gerald Tesauro, Jonathan P How
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Quantized Training of Gradient Boosting Decision Trees Yu Shi, Guolin Ke, Zhuoming Chen, Shuxin Zheng, Tie-Yan Liu
Main Conference Track
Convergent Representations of Computer Programs in Human and Artificial Neural Networks Shashank Srikant, Ben Lipkin, Anna Ivanova, Evelina Fedorenko, Una-May O'Reilly
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QC-StyleGAN - Quality Controllable Image Generation and Manipulation Dat Viet Thanh Nguyen, Phong Tran The, Tan M. Dinh, Cuong Pham, Anh Tran
Main Conference Track
Retrieve, Reason, and Refine: Generating Accurate and Faithful Patient Instructions Fenglin Liu, Bang Yang, Chenyu You, Xian Wu, Shen Ge, Zhangdaihong Liu, Xu Sun, Yang Yang, David Clifton
Main Conference Track
Data Distributional Properties Drive Emergent In-Context Learning in Transformers Stephanie Chan, Adam Santoro, Andrew Lampinen, Jane Wang, Aaditya Singh, Pierre Richemond, James L. McClelland, Felix Hill
Main Conference Track
Algorithms that Approximate Data Removal: New Results and Limitations Vinith Suriyakumar, Ashia C Wilson
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LOT: Layer-wise Orthogonal Training on Improving l2 Certified Robustness Xiaojun Xu, Linyi Li, Bo Li
Main Conference Track
Lottery Tickets on a Data Diet: Finding Initializations with Sparse Trainable Networks Mansheej Paul, Brett Larsen, Surya Ganguli, Jonathan Frankle, Gintare Karolina Dziugaite
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Regularized Molecular Conformation Fields Lihao Wang, Yi Zhou, Yiqun Wang, Xiaoqing Zheng, Xuanjing Huang, Hao Zhou
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Reconstruction on Trees and Low-Degree Polynomials Frederic Koehler, Elchanan Mossel
Main Conference Track
Lower Bounds and Nearly Optimal Algorithms in Distributed Learning with Communication Compression Xinmeng Huang, Yiming Chen, Wotao Yin, Kun Yuan
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Memory safe computations with XLA compiler Artem Artemev, Yuze An, Tilman Roeder, Mark van der Wilk
Main Conference Track
Towards Theoretically Inspired Neural Initialization Optimization Yibo Yang, Hong Wang, Haobo Yuan, Zhouchen Lin
Main Conference Track
AnimeRun: 2D Animation Visual Correspondence from Open Source 3D Movies Li Siyao, Yuhang Li, Bo Li, Chao Dong, Ziwei Liu, Chen Change Loy
Datasets and Benchmarks Track
Uncertainty Estimation Using Riemannian Model Dynamics for Offline Reinforcement Learning Guy Tennenholtz, Shie Mannor
Main Conference Track
Improved Convergence Rate of Stochastic Gradient Langevin Dynamics with Variance Reduction and its Application to Optimization Yuri Kinoshita, Taiji Suzuki
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Practical Adversarial Attacks on Spatiotemporal Traffic Forecasting Models Fan LIU, Hao Liu, Wenzhao Jiang
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Efficient learning of nonlinear prediction models with time-series privileged information Bastian Jung, Fredrik D Johansson
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Layer Freezing & Data Sieving: Missing Pieces of a Generic Framework for Sparse Training Geng Yuan, Yanyu Li, Sheng Li, Zhenglun Kong, Sergey Tulyakov, Xulong Tang, Yanzhi Wang, Jian Ren
Main Conference Track
ETAB: A Benchmark Suite for Visual Representation Learning in Echocardiography Ahmed M. Alaa, Anthony Philippakis, David Sontag
Datasets and Benchmarks Track
Trustworthy Monte Carlo Juha Harviainen, Mikko Koivisto, Petteri Kaski
Main Conference Track
Double Bubble, Toil and Trouble: Enhancing Certified Robustness through Transitivity Andrew Cullen, Paul Montague, Shijie Liu, Sarah Erfani, Benjamin I. Rubinstein
Main Conference Track
An $\alpha$-No-Regret Algorithm For Graphical Bilinear Bandits Geovani Rizk, Igor Colin, Albert Thomas, Rida Laraki, Yann Chevaleyre
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A Unified Analysis of Federated Learning with Arbitrary Client Participation Shiqiang Wang, Mingyue Ji
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Deconfounded Representation Similarity for Comparison of Neural Networks Tianyu Cui, Yogesh Kumar, Pekka Marttinen, Samuel Kaski
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Fairness without Demographics through Knowledge Distillation Junyi Chai, Taeuk Jang, Xiaoqian Wang
Main Conference Track
Sleeper Agent: Scalable Hidden Trigger Backdoors for Neural Networks Trained from Scratch Hossein Souri, Liam Fowl, Rama Chellappa, Micah Goldblum, Tom Goldstein
Main Conference Track
Dynamic Pricing with Monotonicity Constraint under Unknown Parametric Demand Model Su Jia, Andrew Li, R Ravi
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A Win-win Deal: Towards Sparse and Robust Pre-trained Language Models Yuanxin Liu, Fandong Meng, Zheng Lin, Jiangnan Li, Peng Fu, Yanan Cao, Weiping Wang, Jie Zhou
Main Conference Track
Asymptotics of smoothed Wasserstein distances in the small noise regime Yunzi Ding, Jonathan Niles-Weed
Main Conference Track
Fine-tuning Language Models over Slow Networks using Activation Quantization with Guarantees Jue WANG, Binhang Yuan, Luka Rimanic, Yongjun He, Tri Dao, Beidi Chen, Christopher Ré, Ce Zhang
Main Conference Track
Pareto Set Learning for Expensive Multi-Objective Optimization Xi Lin, Zhiyuan Yang, Xiaoyuan Zhang, Qingfu Zhang
Main Conference Track
Non-monotonic Resource Utilization in the Bandits with Knapsacks Problem Raunak Kumar, Robert D. Kleinberg
Main Conference Track
Efficient identification of informative features in simulation-based inference Jonas Beck, Michael Deistler, Yves Bernaerts, Jakob H Macke, Philipp Berens
Main Conference Track
Agreement-on-the-line: Predicting the Performance of Neural Networks under Distribution Shift Christina Baek, Yiding Jiang, Aditi Raghunathan, J. Zico Kolter
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Large-Scale Differentiable Causal Discovery of Factor Graphs Romain Lopez, Jan-Christian Huetter, Jonathan Pritchard, Aviv Regev
Main Conference Track
Diagnosing failures of fairness transfer across distribution shift in real-world medical settings Jessica Schrouff, Natalie Harris, Sanmi Koyejo, Ibrahim M Alabdulmohsin, Eva Schnider, Krista Opsahl-Ong, Alexander Brown, Subhrajit Roy, Diana Mincu, Christina Chen, Awa Dieng, Yuan Liu, Vivek Natarajan, Alan Karthikesalingam, Katherine A. Heller, Silvia Chiappa, Alexander D'Amour
Main Conference Track
Towards Lightweight Black-Box Attack Against Deep Neural Networks Chenghao Sun, Yonggang Zhang, Wan Chaoqun, Qizhou Wang, Ya Li, Tongliang Liu, Bo Han, Xinmei Tian
Main Conference Track
Federated Learning from Pre-Trained Models: A Contrastive Learning Approach Yue Tan, Guodong Long, Jie Ma, LU LIU, Tianyi Zhou, Jing Jiang
Main Conference Track
Theoretically Provable Spiking Neural Networks Shao-Qun Zhang, Zhi-Hua Zhou
Main Conference Track
Approximate Euclidean lengths and distances beyond Johnson-Lindenstrauss Aleksandros Sobczyk, Mathieu Luisier
Main Conference Track
InsPro: Propagating Instance Query and Proposal for Online Video Instance Segmentation Fei He, Haoyang Zhang, Naiyu Gao, Jian Jia, Yanhu Shan, Xin Zhao, Kaiqi Huang
Main Conference Track
Measuring and Reducing Model Update Regression in Structured Prediction for NLP Deng Cai, Elman Mansimov, Yi-An Lai, Yixuan Su, Lei Shu, Yi Zhang
Main Conference Track
Rethinking Lipschitz Neural Networks and Certified Robustness: A Boolean Function Perspective Bohang Zhang, Du Jiang, Di He, Liwei Wang
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Multivariate Time-Series Forecasting with Temporal Polynomial Graph Neural Networks Yijing Liu, Qinxian Liu, Jian-Wei Zhang, Haozhe Feng, Zhongwei Wang, Zihan Zhou, Wei Chen
Main Conference Track
Few-shot Image Generation via Adaptation-Aware Kernel Modulation Yunqing Zhao, Keshigeyan Chandrasegaran, Milad Abdollahzadeh, Ngai-Man (Man) Cheung
Main Conference Track
Learning to Follow Instructions in Text-Based Games Mathieu Tuli, Andrew Li, Pashootan Vaezipoor, Toryn Klassen, Scott Sanner, Sheila McIlraith
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Concentration of Data Encoding in Parameterized Quantum Circuits Guangxi Li, Ruilin Ye, Xuanqiang Zhao, Xin Wang
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Improving Variational Autoencoders with Density Gap-based Regularization Jianfei Zhang, Jun Bai, Chenghua Lin, Yanmeng Wang, Wenge Rong
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RISE: Robust Individualized Decision Learning with Sensitive Variables Xiaoqing Tan, Zhengling Qi, Christopher Seymour, Lu Tang
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Bayesian Clustering of Neural Spiking Activity Using a Mixture of Dynamic Poisson Factor Analyzers Ganchao Wei, Ian H Stevenson, Xiaojing Wang
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Understanding Deep Contrastive Learning via Coordinate-wise Optimization Yuandong Tian
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Beyond neural scaling laws: beating power law scaling via data pruning Ben Sorscher, Robert Geirhos, Shashank Shekhar, Surya Ganguli, Ari Morcos
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Neural Estimation of Submodular Functions with Applications to Differentiable Subset Selection Abir De, Soumen Chakrabarti
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Maximum Class Separation as Inductive Bias in One Matrix Tejaswi Kasarla, Gertjan Burghouts, Max van Spengler, Elise van der Pol, Rita Cucchiara, Pascal Mettes
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Surprising Instabilities in Training Deep Networks and a Theoretical Analysis Yuxin Sun, DONG LAO, Ganesh Sundaramoorthi, Anthony Yezzi
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WaveBound: Dynamic Error Bounds for Stable Time Series Forecasting Youngin Cho, Daejin Kim, DONGMIN KIM, MOHAMMAD AZAM KHAN, Jaegul Choo
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Finite-Time Analysis of Adaptive Temporal Difference Learning with Deep Neural Networks Tao Sun, Dongsheng Li, Bao Wang
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Benign Underfitting of Stochastic Gradient Descent Tomer Koren, Roi Livni, Yishay Mansour, Uri Sherman
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A Geometric Perspective on Variational Autoencoders Clément Chadebec, Stephanie Allassonniere
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A Data-Augmentation Is Worth A Thousand Samples: Analytical Moments And Sampling-Free Training Randall Balestriero, Ishan Misra, Yann LeCun
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Effective Adaptation in Multi-Task Co-Training for Unified Autonomous Driving Xiwen Liang, Yangxin Wu, Jianhua Han, Hang Xu, Chunjing XU, Xiaodan Liang
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Redundant representations help generalization in wide neural networks Diego Doimo, Aldo Glielmo, Sebastian Goldt, Alessandro Laio
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Mean Estimation in High-Dimensional Binary Markov Gaussian Mixture Models Yihan Zhang, Nir Weinberger
Main Conference Track
Rate-Distortion Theoretic Bounds on Generalization Error for Distributed Learning Milad Sefidgaran, Romain Chor, Abdellatif Zaidi
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Online Frank-Wolfe with Arbitrary Delays Yuanyu Wan, Wei-Wei Tu, Lijun Zhang
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Isometric 3D Adversarial Examples in the Physical World yibo miao, Yinpeng Dong, Jun Zhu, Xiao-Shan Gao
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Tight Lower Bounds on Worst-Case Guarantees for Zero-Shot Learning with Attributes Alessio Mazzetto, Cristina Menghini, Andrew Yuan, Eli Upfal, Stephen Bach
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Graph Neural Networks with Adaptive Readouts David Buterez, Jon Paul Janet, Steven J Kiddle, Dino Oglic, Pietro Liò
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Robust Imitation of a Few Demonstrations with a Backwards Model Jung Yeon Park, Lawson Wong
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Communication Efficient Distributed Learning for Kernelized Contextual Bandits Chuanhao Li, Huazheng Wang, Mengdi Wang, Hongning Wang
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Trust Region Policy Optimization with Optimal Transport Discrepancies: Duality and Algorithm for Continuous Actions Antonio Terpin, Nicolas Lanzetti, Batuhan Yardim, Florian Dorfler, Giorgia Ramponi
Main Conference Track
ELIAS: End-to-End Learning to Index and Search in Large Output Spaces Nilesh Gupta, Patrick Chen, Hsiang-Fu Yu, Cho-Jui Hsieh, Inderjit S. Dhillon
Main Conference Track
GStarX: Explaining Graph Neural Networks with Structure-Aware Cooperative Games Shichang Zhang, Yozen Liu, Neil Shah, Yizhou Sun
Main Conference Track
Bridging the Gap from Asymmetry Tricks to Decorrelation Principles in Non-contrastive Self-supervised Learning Kang-Jun Liu, Masanori Suganuma, Takayuki Okatani
Main Conference Track
Lipschitz Bandits with Batched Feedback Yasong Feng, zengfeng Huang, Tianyu Wang
Main Conference Track
Improving Barely Supervised Learning by Discriminating Unlabeled Samples with Super-Class Guan Gui, Zhen Zhao, Lei Qi, Luping Zhou, Lei Wang, Yinghuan Shi
Main Conference Track
Low-Rank Modular Reinforcement Learning via Muscle Synergy Heng Dong, Tonghan Wang, Jiayuan Liu, Chongjie Zhang
Main Conference Track
Neural Temporal Walks: Motif-Aware Representation Learning on Continuous-Time Dynamic Graphs Ming Jin, Yuan-Fang Li, Shirui Pan
Main Conference Track
Understanding Benign Overfitting in Gradient-Based Meta Learning Lisha Chen, Songtao Lu, Tianyi Chen
Main Conference Track
Generative Neural Articulated Radiance Fields Alexander Bergman, Petr Kellnhofer, Wang Yifan, Eric Chan, David Lindell, Gordon Wetzstein
Main Conference Track
AutoMS: Automatic Model Selection for Novelty Detection with Error Rate Control Yifan Zhang, Haiyan Jiang, Haojie Ren, Changliang Zou, Dejing Dou
Main Conference Track
GALOIS: Boosting Deep Reinforcement Learning via Generalizable Logic Synthesis Yushi Cao, Zhiming Li, Tianpei Yang, Hao Zhang, YAN ZHENG, Yi Li, Jianye Hao, Yang Liu
Main Conference Track
Faster Deep Reinforcement Learning with Slower Online Network Kavosh Asadi, Rasool Fakoor, Omer Gottesman, Taesup Kim, Michael L. Littman, Alexander J Smola
Main Conference Track
Learn to Match with No Regret: Reinforcement Learning in Markov Matching Markets Yifei Min, Tianhao Wang, Ruitu Xu, Zhaoran Wang, Michael I. Jordan, Zhuoran Yang
Main Conference Track
Efficient Frameworks for Generalized Low-Rank Matrix Bandit Problems Yue Kang, Cho-Jui Hsieh, Thomas Chun Man Lee
Main Conference Track
A Projection-free Algorithm for Constrained Stochastic Multi-level Composition Optimization Tesi Xiao, Krishnakumar Balasubramanian, Saeed Ghadimi
Main Conference Track
Green Hierarchical Vision Transformer for Masked Image Modeling Lang Huang, Shan You, Mingkai Zheng, Fei Wang, Chen Qian, Toshihiko Yamasaki
Main Conference Track
Simultaneous Missing Value Imputation and Structure Learning with Groups Pablo Morales-Alvarez, Wenbo Gong, Angus Lamb, Simon Woodhead, Simon Peyton Jones, Nick Pawlowski, Miltiadis Allamanis, Cheng Zhang
Main Conference Track
Towards Reliable Simulation-Based Inference with Balanced Neural Ratio Estimation Arnaud Delaunoy, Joeri Hermans, François Rozet, Antoine Wehenkel, Gilles Louppe
Main Conference Track
Interaction Modeling with Multiplex Attention Fan-Yun Sun, Isaac Kauvar, Ruohan Zhang, Jiachen Li, Mykel J Kochenderfer, Jiajun Wu, Nick Haber
Main Conference Track
Low-rank lottery tickets: finding efficient low-rank neural networks via matrix differential equations Steffen Schotthöfer, Emanuele Zangrando, Jonas Kusch, Gianluca Ceruti, Francesco Tudisco
Main Conference Track
Causality-driven Hierarchical Structure Discovery for Reinforcement Learning shaohui peng, Xing Hu, Rui Zhang, Ke Tang, Jiaming Guo, Qi Yi, Ruizhi Chen, xishan zhang, Zidong Du, Ling Li, Qi Guo, Yunji Chen
Main Conference Track
Pay attention to your loss : understanding misconceptions about Lipschitz neural networks Louis Béthune, Thibaut Boissin, Mathieu Serrurier, Franck Mamalet, Corentin Friedrich, Alberto Gonzalez Sanz
Main Conference Track
Large-Scale Retrieval for Reinforcement Learning Peter Humphreys, Arthur Guez, Olivier Tieleman, Laurent Sifre, Theophane Weber, Timothy Lillicrap
Main Conference Track
Gradient flow dynamics of shallow ReLU networks for square loss and orthogonal inputs Etienne Boursier, Loucas PILLAUD-VIVIEN, Nicolas Flammarion
Main Conference Track
Weisfeiler and Leman Go Walking: Random Walk Kernels Revisited Nils M. Kriege
Main Conference Track
Outsourcing Training without Uploading Data via Efficient Collaborative Open-Source Sampling Junyuan Hong, Lingjuan Lyu, Jiayu Zhou, Michael Spranger
Main Conference Track
Multi-agent Dynamic Algorithm Configuration Ke Xue, Jiacheng Xu, Lei Yuan, Miqing Li, Chao Qian, Zongzhang Zhang, Yang Yu
Main Conference Track
TaSIL: Taylor Series Imitation Learning Daniel Pfrommer, Thomas Zhang, Stephen Tu, Nikolai Matni
Main Conference Track
Experimental Design for Linear Functionals in Reproducing Kernel Hilbert Spaces Mojmir Mutny, Andreas Krause
Main Conference Track
Continuous MDP Homomorphisms and Homomorphic Policy Gradient Sahand Rezaei-Shoshtari, Rosie Zhao, Prakash Panangaden, David Meger, Doina Precup
Main Conference Track
Score-based Generative Modeling Secretly Minimizes the Wasserstein Distance Dohyun Kwon, Ying Fan, Kangwook Lee
Main Conference Track
Uncertainty-Aware Reinforcement Learning for Risk-Sensitive Player Evaluation in Sports Game Guiliang Liu, Yudong Luo, Oliver Schulte, Pascal Poupart
Main Conference Track
End-to-end Algorithm Synthesis with Recurrent Networks: Extrapolation without Overthinking Arpit Bansal, Avi Schwarzschild, Eitan Borgnia, Zeyad Emam, Furong Huang, Micah Goldblum, Tom Goldstein
Main Conference Track
Smooth Fictitious Play in Stochastic Games with Perturbed Payoffs and Unknown Transitions Lucas Baudin, Rida Laraki
Main Conference Track
OOD Link Prediction Generalization Capabilities of Message-Passing GNNs in Larger Test Graphs Yangze Zhou, Gitta Kutyniok, Bruno Ribeiro
Main Conference Track
Algorithms with Prediction Portfolios Michael Dinitz, Sungjin Im, Thomas Lavastida, Benjamin Moseley, Sergei Vassilvitskii
Main Conference Track
A Unified Hard-Constraint Framework for Solving Geometrically Complex PDEs Songming Liu, Hao Zhongkai, Chengyang Ying, Hang Su, Jun Zhu, Ze Cheng
Main Conference Track
Instability and Local Minima in GAN Training with Kernel Discriminators Evan Becker, Parthe Pandit, Sundeep Rangan, Alyson K. Fletcher
Main Conference Track
Versatile Multi-stage Graph Neural Network for Circuit Representation Shuwen Yang, Zhihao Yang, Dong Li, Yingxueff Zhang, Zhanguang Zhang, Guojie Song, Jianye Hao
Main Conference Track
Non-Stationary Bandits under Recharging Payoffs: Improved Planning with Sublinear Regret Orestis Papadigenopoulos, Constantine Caramanis, Sanjay Shakkottai
Main Conference Track
Optimal and Adaptive Monteiro-Svaiter Acceleration Yair Carmon, Danielle Hausler, Arun Jambulapati, Yujia Jin, Aaron Sidford
Main Conference Track
Chroma-VAE: Mitigating Shortcut Learning with Generative Classifiers Wanqian Yang, Polina Kirichenko, Micah Goldblum, Andrew G Wilson
Main Conference Track
SparCL: Sparse Continual Learning on the Edge Zifeng Wang, Zheng Zhan, Yifan Gong, Geng Yuan, Wei Niu, Tong Jian, Bin Ren, Stratis Ioannidis, Yanzhi Wang, Jennifer Dy
Main Conference Track
Adaptively Exploiting d-Separators with Causal Bandits Blair Bilodeau, Linbo Wang, Dan Roy
Main Conference Track
Spectrum Random Masking for Generalization in Image-based Reinforcement Learning Yangru Huang, Peixi Peng, Yifan Zhao, Guangyao Chen, Yonghong Tian
Main Conference Track
Contrastive Graph Structure Learning via Information Bottleneck for Recommendation Chunyu Wei, Jian Liang, Di Liu, Fei Wang
Main Conference Track
Pyramid Attention For Source Code Summarization Lei Chai, Ming LI
Main Conference Track
SIREN: Shaping Representations for Detecting Out-of-Distribution Objects Xuefeng Du, Gabriel Gozum, Yifei Ming, Yixuan Li
Main Conference Track
CLOOB: Modern Hopfield Networks with InfoLOOB Outperform CLIP Andreas Fürst, Elisabeth Rumetshofer, Johannes Lehner, Viet T. Tran, Fei Tang, Hubert Ramsauer, David Kreil, Michael Kopp, Günter Klambauer, Angela Bitto, Sepp Hochreiter
Main Conference Track
I2Q: A Fully Decentralized Q-Learning Algorithm Jiechuan Jiang, Zongqing Lu
Main Conference Track
Planning to the Information Horizon of BAMDPs via Epistemic State Abstraction Dilip Arumugam, Satinder P. Singh
Main Conference Track
AutoST: Towards the Universal Modeling of Spatio-temporal Sequences Jianxin Li, Shuai Zhang, Hui Xiong, Haoyi Zhou
Main Conference Track
Constrained Langevin Algorithms with L-mixing External Random Variables Yuping Zheng, Andrew Lamperski
Main Conference Track
Language Conditioned Spatial Relation Reasoning for 3D Object Grounding Shizhe Chen, Pierre-Louis Guhur, Makarand Tapaswi, Cordelia Schmid, Ivan Laptev
Main Conference Track
MVP-N: A Dataset and Benchmark for Real-World Multi-View Object Classification REN WANG, Jiayue Wang, Tae Sung Kim, JINSUNG KIM, Hyuk-Jae Lee
Datasets and Benchmarks Track
Data Augmentation for Compositional Data: Advancing Predictive Models of the Microbiome Elliott Gordon-Rodriguez, Thomas Quinn, John P. Cunningham
Main Conference Track
On the Robustness of Deep Clustering Models: Adversarial Attacks and Defenses Anshuman Chhabra, Ashwin Sekhari, Prasant Mohapatra
Main Conference Track
Exploiting the Relationship Between Kendall's Rank Correlation and Cosine Similarity for Attribution Protection Fan Wang, Adams Wai Kin Kong
Main Conference Track
Wavelet Feature Maps Compression for Image-to-Image CNNs Shahaf E. Finder, Yair Zohav, Maor Ashkenazi, Eran Treister
Main Conference Track
Biologically plausible solutions for spiking networks with efficient coding Veronika Koren, Stefano Panzeri
Main Conference Track
Finding Optimal Arms in Non-stochastic Combinatorial Bandits with Semi-bandit Feedback and Finite Budget Jasmin Brandt, Viktor Bengs, Björn Haddenhorst, Eyke Hüllermeier
Main Conference Track
Graph Neural Networks are Dynamic Programmers Andrew J Dudzik, Petar Veličković
Main Conference Track
Evaluated CMI Bounds for Meta Learning: Tightness and Expressiveness Fredrik Hellström, Giuseppe Durisi
Main Conference Track
SPD: Synergy Pattern Diversifying Oriented Unsupervised Multi-agent Reinforcement Learning Yuhang Jiang, Jianzhun Shao, Shuncheng He, Hongchang Zhang, Xiangyang Ji
Main Conference Track
Self-Aware Personalized Federated Learning Huili Chen, Jie Ding, Eric W. Tramel, Shuang Wu, Anit Kumar Sahu, Salman Avestimehr, Tao Zhang
Main Conference Track
Additive MIL: Intrinsically Interpretable Multiple Instance Learning for Pathology Syed Ashar Javed, Dinkar Juyal, Harshith Padigela, Amaro Taylor-Weiner, Limin Yu, Aaditya Prakash
Main Conference Track
Model-Based Imitation Learning for Urban Driving Anthony Hu, Gianluca Corrado, Nicolas Griffiths, Zachary Murez, Corina Gurau, Hudson Yeo, Alex Kendall, Roberto Cipolla, Jamie Shotton
Main Conference Track
Online Training Through Time for Spiking Neural Networks Mingqing Xiao, Qingyan Meng, Zongpeng Zhang, Di He, Zhouchen Lin
Main Conference Track
SCONE: Surface Coverage Optimization in Unknown Environments by Volumetric Integration Antoine Guedon, Pascal Monasse, Vincent Lepetit
Main Conference Track
WebShop: Towards Scalable Real-World Web Interaction with Grounded Language Agents Shunyu Yao, Howard Chen, John Yang, Karthik Narasimhan
Main Conference Track
Boosting Out-of-distribution Detection with Typical Features Yao Zhu, YueFeng Chen, Chuanlong Xie, Xiaodan Li, Rong Zhang, Hui Xue', Xiang Tian, bolun zheng, Yaowu Chen
Main Conference Track
Dynamic Learning in Large Matching Markets Anand Kalvit, Assaf J. Zeevi
Main Conference Track
Invariant and Transportable Representations for Anti-Causal Domain Shifts Yibo Jiang, Victor Veitch
Main Conference Track
Symplectic Spectrum Gaussian Processes: Learning Hamiltonians from Noisy and Sparse Data Yusuke Tanaka, Tomoharu Iwata, naonori ueda
Main Conference Track
Multiclass Learnability Beyond the PAC Framework: Universal Rates and Partial Concept Classes Alkis Kalavasis, Grigoris Velegkas, Amin Karbasi
Main Conference Track
MetaTeacher: Coordinating Multi-Model Domain Adaptation for Medical Image Classification Zhenbin Wang, Mao Ye, Xiatian Zhu, Liuhan Peng, Liang Tian, Yingying Zhu
Main Conference Track
Biological Learning of Irreducible Representations of Commuting Transformations Alexander Genkin, David Lipshutz, Siavash Golkar, Tiberiu Tesileanu, Dmitri B. Chklovskii
Main Conference Track
A Fourier Approach to Mixture Learning Mingda Qiao, Guru Guruganesh, Ankit Rawat, Kumar Avinava Dubey, Manzil Zaheer
Main Conference Track
Structured Energy Network As a Loss Jay Yoon Lee, Dhruvesh Patel, Purujit Goyal, Wenlong Zhao, Zhiyang Xu, Andrew McCallum
Main Conference Track
Bayesian inference via sparse Hamiltonian flows Naitong Chen, Zuheng Xu, Trevor Campbell
Main Conference Track
SAPA: Similarity-Aware Point Affiliation for Feature Upsampling Hao Lu, Wenze Liu, Zixuan Ye, Hongtao Fu, Yuliang Liu, Zhiguo Cao
Main Conference Track
Losses Can Be Blessings: Routing Self-Supervised Speech Representations Towards Efficient Multilingual and Multitask Speech Processing Yonggan Fu, Yang Zhang, Kaizhi Qian, Zhifan Ye, Zhongzhi Yu, Cheng-I Jeff Lai, Celine Lin
Main Conference Track
Gradient Methods Provably Converge to Non-Robust Networks Gal Vardi, Gilad Yehudai, Ohad Shamir
Main Conference Track
Diversity vs. Recognizability: Human-like generalization in one-shot generative models Victor Boutin, Lakshya Singhal, Xavier Thomas, Thomas Serre
Main Conference Track
Task-level Differentially Private Meta Learning Xinyu Zhou, Raef Bassily
Main Conference Track
On the Statistical Efficiency of Reward-Free Exploration in Non-Linear RL Jinglin Chen, Aditya Modi, Akshay Krishnamurthy, Nan Jiang, Alekh Agarwal
Main Conference Track
Pessimism for Offline Linear Contextual Bandits using $\ell_p$ Confidence Sets Gene Li, Cong Ma, Nati Srebro
Main Conference Track
Discrete-Convex-Analysis-Based Framework for Warm-Starting Algorithms with Predictions Shinsaku Sakaue, Taihei Oki
Main Conference Track
CAESAR: An Embodied Simulator for Generating Multimodal Referring Expression Datasets Md Mofijul Islam, Reza Mirzaiee, Alexi Gladstone, Haley Green, Tariq Iqbal
Datasets and Benchmarks Track
Generalizing Bayesian Optimization with Decision-theoretic Entropies Willie Neiswanger, Lantao Yu, Shengjia Zhao, Chenlin Meng, Stefano Ermon
Main Conference Track
Ordered Subgraph Aggregation Networks Chendi Qian, Gaurav Rattan, Floris Geerts, Mathias Niepert, Christopher Morris
Main Conference Track
Neuron with Steady Response Leads to Better Generalization Qiang Fu, Lun Du, Haitao Mao, Xu Chen, Wei Fang, Shi Han, Dongmei Zhang
Main Conference Track
Laplacian Autoencoders for Learning Stochastic Representations Marco Miani, Frederik Warburg, Pablo Moreno-Muñoz, Nicki Skafte, Søren Hauberg
Main Conference Track
Alleviating the Sample Selection Bias in Few-shot Learning by Removing Projection to the Centroid Jing Xu, Xu Luo, Xinglin Pan, Yanan Li, Wenjie Pei, Zenglin Xu
Main Conference Track
A Coupled Design of Exploiting Record Similarity for Practical Vertical Federated Learning Zhaomin Wu, Qinbin Li, Bingsheng He
Main Conference Track
Cooperative Distribution Alignment via JSD Upper Bound Wonwoong Cho, ZIYU GONG, David I Inouye
Main Conference Track
An Analytical Theory of Curriculum Learning in Teacher-Student Networks Luca Saglietti, Stefano Mannelli, Andrew Saxe
Main Conference Track
RSA: Reducing Semantic Shift from Aggressive Augmentations for Self-supervised Learning Yingbin Bai, Erkun Yang, Zhaoqing Wang, Yuxuan Du, Bo Han, Cheng Deng, Dadong Wang, Tongliang Liu
Main Conference Track
Evaluating Latent Space Robustness and Uncertainty of EEG-ML Models under Realistic Distribution Shifts Neeraj Wagh, Jionghao Wei, Samarth Rawal, Brent M Berry, Yogatheesan Varatharajah
Main Conference Track
u-HuBERT: Unified Mixed-Modal Speech Pretraining And Zero-Shot Transfer to Unlabeled Modality Wei-Ning Hsu, Bowen Shi
Main Conference Track
Hierarchical Graph Transformer with Adaptive Node Sampling ZAIXI ZHANG, Qi Liu, Qingyong Hu, Chee-Kong Lee
Main Conference Track
Learning Options via Compression Yiding Jiang, Evan Liu, Benjamin Eysenbach, J. Zico Kolter, Chelsea Finn
Main Conference Track
Fixed-Distance Hamiltonian Monte Carlo Hadi Mohasel Afshar, Sally Cripps
Main Conference Track
GlanceNets: Interpretable, Leak-proof Concept-based Models Emanuele Marconato, Andrea Passerini, Stefano Teso
Main Conference Track
3DOS: Towards 3D Open Set Learning - Benchmarking and Understanding Semantic Novelty Detection on Point Clouds Antonio Alliegro, Francesco Cappio Borlino, Tatiana Tommasi
Datasets and Benchmarks Track
Masked Prediction: A Parameter Identifiability View Bingbin Liu, Daniel J. Hsu, Pradeep K. Ravikumar, Andrej Risteski
Main Conference Track
Self-Supervised Learning of Brain Dynamics from Broad Neuroimaging Data Armin Thomas, Christopher Ré, Russell Poldrack
Main Conference Track
Characterization of Excess Risk for Locally Strongly Convex Population Risk Mingyang Yi, Ruoyu Wang, Zhi-Ming Ma
Main Conference Track
A Non-Asymptotic Moreau Envelope Theory for High-Dimensional Generalized Linear Models Lijia Zhou, Frederic Koehler, Pragya Sur, Danica J. Sutherland, Nati Srebro
Main Conference Track
Towards Efficient 3D Object Detection with Knowledge Distillation Jihan Yang, Shaoshuai Shi, Runyu Ding, Zhe Wang, Xiaojuan Qi
Main Conference Track
CodeRL: Mastering Code Generation through Pretrained Models and Deep Reinforcement Learning Hung Le, Yue Wang, Akhilesh Deepak Gotmare, Silvio Savarese, Steven Chu Hong Hoi
Main Conference Track
Leveraging the Hints: Adaptive Bidding in Repeated First-Price Auctions Wei Zhang, Yanjun Han, Zhengyuan Zhou, Aaron Flores, Tsachy Weissman
Main Conference Track
Sample Efficiency Matters: A Benchmark for Practical Molecular Optimization Wenhao Gao, Tianfan Fu, Jimeng Sun, Connor Coley
Datasets and Benchmarks Track
MGNNI: Multiscale Graph Neural Networks with Implicit Layers Juncheng Liu, Bryan Hooi, Kenji Kawaguchi, Xiaokui Xiao
Main Conference Track
UQGAN: A Unified Model for Uncertainty Quantification of Deep Classifiers trained via Conditional GANs Philipp Oberdiek, Gernot Fink, Matthias Rottmann
Main Conference Track
Audio-Driven Co-Speech Gesture Video Generation Xian Liu, Qianyi Wu, Hang Zhou, Yuanqi Du, Wayne Wu, Dahua Lin, Ziwei Liu
Main Conference Track
Concept Embedding Models: Beyond the Accuracy-Explainability Trade-Off Mateo Espinosa Zarlenga, Pietro Barbiero, Gabriele Ciravegna, Giuseppe Marra, Francesco Giannini, Michelangelo Diligenti, Zohreh Shams, Frederic Precioso, Stefano Melacci, Adrian Weller, Pietro Lió, Mateja Jamnik
Main Conference Track
DENSE: Data-Free One-Shot Federated Learning Jie Zhang, Chen Chen, Bo Li, Lingjuan Lyu, Shuang Wu, Shouhong Ding, Chunhua Shen, Chao Wu
Main Conference Track
Searching for Better Spatio-temporal Alignment in Few-Shot Action Recognition Yichao Cao, Xiu Su, Qingfei Tang, Shan You, Xiaobo Lu, Chang Xu
Main Conference Track
Fine-Tuning Pre-Trained Language Models Effectively by Optimizing Subnetworks Adaptively Haojie Zhang, Ge Li, Jia Li, Zhongjin Zhang, YUQI ZHU, Zhi Jin
Main Conference Track
Quality Not Quantity: On the Interaction between Dataset Design and Robustness of CLIP Thao Nguyen, Gabriel Ilharco, Mitchell Wortsman, Sewoong Oh, Ludwig Schmidt
Main Conference Track
Stars: Tera-Scale Graph Building for Clustering and Learning CJ Carey, Jonathan Halcrow, Rajesh Jayaram, Vahab Mirrokni, Warren Schudy, Peilin Zhong
Main Conference Track
Score-Based Diffusion meets Annealed Importance Sampling Arnaud Doucet, Will Grathwohl, Alexander G Matthews, Heiko Strathmann
Main Conference Track
PaCo: Parameter-Compositional Multi-task Reinforcement Learning Lingfeng Sun, Haichao Zhang, Wei Xu, Masayoshi TOMIZUKA
Main Conference Track
Entropy-Driven Mixed-Precision Quantization for Deep Network Design Zhenhong Sun, Ce Ge, Junyan Wang, Ming Lin, Hesen Chen, Hao Li, Xiuyu Sun
Main Conference Track
Non-Gaussian Tensor Programs Eugene Golikov, Greg Yang
Main Conference Track
Adaptation Accelerating Sampling-based Bayesian Inference in Attractor Neural Networks Xingsi Dong, Zilong Ji, Tianhao Chu, Tiejun Huang, Wenhao Zhang, Si Wu
Main Conference Track
A Contrastive Framework for Neural Text Generation Yixuan Su, Tian Lan, Yan Wang, Dani Yogatama, Lingpeng Kong, Nigel Collier
Main Conference Track
Exploring the Latent Space of Autoencoders with Interventional Assays Felix Leeb, Stefan Bauer, Michel Besserve, Bernhard Schölkopf
Main Conference Track
Pythae: Unifying Generative Autoencoders in Python - A Benchmarking Use Case Clément Chadebec, Louis Vincent, Stephanie Allassonniere
Datasets and Benchmarks Track
Adaptive Multi-stage Density Ratio Estimation for Learning Latent Space Energy-based Model Zhisheng Xiao, Tian Han
Main Conference Track
An Analysis of Ensemble Sampling Chao Qin, Zheng Wen, Xiuyuan Lu, Benjamin Van Roy
Main Conference Track
Fair Wrapping for Black-box Predictions Alexander Soen, Ibrahim M Alabdulmohsin, Sanmi Koyejo, Yishay Mansour, Nyalleng Moorosi, Richard Nock, Ke Sun, Lexing Xie
Main Conference Track
Bridging Central and Local Differential Privacy in Data Acquisition Mechanisms Alireza Fallah, Ali Makhdoumi, azarakhsh malekian, Asuman Ozdaglar
Main Conference Track
Meta-Learning Dynamics Forecasting Using Task Inference Rui Wang, Robin Walters, Rose Yu
Main Conference Track
Multi-fidelity Monte Carlo: a pseudo-marginal approach Diana Cai, Ryan P. Adams
Main Conference Track
SAPD+: An Accelerated Stochastic Method for Nonconvex-Concave Minimax Problems Xuan Zhang, Necdet Serhat Aybat, Mert Gurbuzbalaban
Main Conference Track
Contrastive Adapters for Foundation Model Group Robustness Michael Zhang, Christopher Ré
Main Conference Track
Decoupled Context Processing for Context Augmented Language Modeling Zonglin Li, Ruiqi Guo, Sanjiv Kumar
Main Conference Track
LISA: Learning Interpretable Skill Abstractions from Language Divyansh Garg, Skanda Vaidyanath, Kuno Kim, Jiaming Song, Stefano Ermon
Main Conference Track
Accelerated Primal-Dual Gradient Method for Smooth and Convex-Concave Saddle-Point Problems with Bilinear Coupling Dmitry Kovalev, Alexander Gasnikov, Peter Richtarik
Main Conference Track
Diffusion Curvature for Estimating Local Curvature in High Dimensional Data Dhananjay Bhaskar, Kincaid MacDonald, Oluwadamilola Fasina, Dawson Thomas, Bastian Rieck, Ian Adelstein, Smita Krishnaswamy
Main Conference Track
Hidden Progress in Deep Learning: SGD Learns Parities Near the Computational Limit Boaz Barak, Benjamin Edelman, Surbhi Goel, Sham Kakade, Eran Malach, Cyril Zhang
Main Conference Track
One Positive Label is Sufficient: Single-Positive Multi-Label Learning with Label Enhancement Ning Xu, Congyu Qiao, Jiaqi Lv, Xin Geng, Min-Ling Zhang
Main Conference Track
Communication Acceleration of Local Gradient Methods via an Accelerated Primal-Dual Algorithm with an Inexact Prox Abdurakhmon Sadiev, Dmitry Kovalev, Peter Richtarik
Main Conference Track
Aligning individual brains with fused unbalanced Gromov Wasserstein Alexis Thual, Quang Huy TRAN, Tatiana Zemskova, Nicolas Courty, Rémi Flamary, Stanislas Dehaene, Bertrand Thirion
Main Conference Track
This is the way: designing and compiling LEPISZCZE, a comprehensive NLP benchmark for Polish Lukasz Augustyniak, Kamil Tagowski, Albert Sawczyn, Denis Janiak, Roman Bartusiak, Adrian Szymczak, Arkadiusz Janz, Piotr Szymański, Marcin Wątroba, Mikołaj Morzy, Tomasz Kajdanowicz, Maciej Piasecki
Datasets and Benchmarks Track
An In-depth Study of Stochastic Backpropagation Jun Fang, Mingze Xu, Hao Chen, Bing Shuai, Zhuowen Tu, Joseph Tighe
Main Conference Track
Transformer Memory as a Differentiable Search Index Yi Tay, Vinh Tran, Mostafa Dehghani, Jianmo Ni, Dara Bahri, Harsh Mehta, Zhen Qin, Kai Hui, Zhe Zhao, Jai Gupta, Tal Schuster, William W. Cohen, Donald Metzler
Main Conference Track
Insights into Pre-training via Simpler Synthetic Tasks Yuhuai Wu, Felix Li, Percy Liang
Main Conference Track
Last-Iterate Convergence of Optimistic Gradient Method for Monotone Variational Inequalities Eduard Gorbunov, Adrien Taylor, Gauthier Gidel
Main Conference Track
3DILG: Irregular Latent Grids for 3D Generative Modeling Biao Zhang, Matthias Niessner, Peter Wonka
Main Conference Track
Policy Optimization for Markov Games: Unified Framework and Faster Convergence Runyu Zhang, Qinghua Liu, Huan Wang, Caiming Xiong, Na Li, Yu Bai
Main Conference Track
C2FAR: Coarse-to-Fine Autoregressive Networks for Precise Probabilistic Forecasting Shane Bergsma, Tim Zeyl, Javad Rahimipour Anaraki, Lei Guo
Main Conference Track
METS-CoV: A Dataset of Medical Entity and Targeted Sentiment on COVID-19 Related Tweets Peilin Zhou, Zeqiang Wang, Dading Chong, Zhijiang Guo, Yining Hua, Zichang Su, Zhiyang Teng, Jiageng Wu, Jie Yang
Datasets and Benchmarks Track
Respecting Transfer Gap in Knowledge Distillation Yulei Niu, Long Chen, Chang Zhou, Hanwang Zhang
Main Conference Track
Target alignment in truncated kernel ridge regression Arash Amini, Richard Baumgartner, Dai Feng
Main Conference Track
Continual Learning In Environments With Polynomial Mixing Times Matthew Riemer, Sharath Chandra Raparthy, Ignacio Cases, Gopeshh Subbaraj, Maximilian Puelma Touzel, Irina Rish
Main Conference Track
ENS-10: A Dataset For Post-Processing Ensemble Weather Forecasts Saleh Ashkboos, Langwen Huang, Nikoli Dryden, Tal Ben-Nun, Peter Dueben, Lukas Gianinazzi, Luca Kummer, Torsten Hoefler
Datasets and Benchmarks Track
Panchromatic and Multispectral Image Fusion via Alternating Reverse Filtering Network Keyu Yan, Man Zhou, Jie Huang, Feng Zhao, Chengjun Xie, Chongyi Li, Danfeng Hong
Main Conference Track
Unsupervised Cross-Task Generalization via Retrieval Augmentation Bill Yuchen Lin, Kangmin Tan, Chris Miller, Beiwen Tian, Xiang Ren
Main Conference Track
Natural gradient enables fast sampling in spiking neural networks Paul Masset, Jacob Zavatone-Veth, J. Patrick Connor, Venkatesh Murthy, Cengiz Pehlevan
Main Conference Track
Adversarial Auto-Augment with Label Preservation: A Representation Learning Principle Guided Approach Kaiwen Yang, Yanchao Sun, Jiahao Su, Fengxiang He, Xinmei Tian, Furong Huang, Tianyi Zhou, Dacheng Tao
Main Conference Track
Coordinate Linear Variance Reduction for Generalized Linear Programming Chaobing Song, Cheuk Yin Lin, Stephen Wright, Jelena Diakonikolas
Main Conference Track
Probabilistic Missing Value Imputation for Mixed Categorical and Ordered Data Yuxuan Zhao, Alex Townsend, Madeleine Udell
Main Conference Track
Gaussian Copula Embeddings Chien Lu, Jaakko Peltonen
Main Conference Track
SGAM: Building a Virtual 3D World through Simultaneous Generation and Mapping Yuan Shen, Wei-Chiu Ma, Shenlong Wang
Main Conference Track
Finding Naturally Occurring Physical Backdoors in Image Datasets Emily Wenger, Roma Bhattacharjee, Arjun Nitin Bhagoji, Josephine Passananti, Emilio Andere, Heather Zheng, Ben Zhao
Datasets and Benchmarks Track
Unsupervised Representation Learning from Pre-trained Diffusion Probabilistic Models Zijian Zhang, Zhou Zhao, Zhijie Lin
Main Conference Track
Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs Yongqiang Chen, Yonggang Zhang, Yatao Bian, Han Yang, MA Kaili, Binghui Xie, Tongliang Liu, Bo Han, James Cheng
Main Conference Track
To update or not to update? Neurons at equilibrium in deep models Andrea Bragagnolo, Enzo Tartaglione, Marco Grangetto
Main Conference Track
Non-convex online learning via algorithmic equivalence Udaya Ghai, Zhou Lu, Elad Hazan
Main Conference Track
TA-MoE: Topology-Aware Large Scale Mixture-of-Expert Training Chang Chen, Min Li, Zhihua Wu, Dianhai Yu, Chao Yang
Main Conference Track
A Combinatorial Perspective on the Optimization of Shallow ReLU Networks Michael S Matena, Colin A Raffel
Main Conference Track
Large Language Models are Zero-Shot Reasoners Takeshi Kojima, Shixiang (Shane) Gu, Machel Reid, Yutaka Matsuo, Yusuke Iwasawa
Main Conference Track
Trading off Utility, Informativeness, and Complexity in Emergent Communication Mycal Tucker, Roger P. Levy, Julie A Shah, Noga Zaslavsky
Main Conference Track
FiLM-Ensemble: Probabilistic Deep Learning via Feature-wise Linear Modulation Mehmet Ozgur Turkoglu, Alexander Becker, Hüseyin Anil Gündüz, Mina Rezaei, Bernd Bischl, Rodrigo Caye Daudt, Stefano D'Aronco, Jan Wegner, Konrad Schindler
Main Conference Track
Meta-DMoE: Adapting to Domain Shift by Meta-Distillation from Mixture-of-Experts Tao Zhong, Zhixiang Chi, Li Gu, Yang Wang, Yuanhao Yu, Jin Tang
Main Conference Track
Beyond Time-Average Convergence: Near-Optimal Uncoupled Online Learning via Clairvoyant Multiplicative Weights Update Georgios Piliouras, Ryann Sim, Stratis Skoulakis
Main Conference Track
Meta-Reward-Net: Implicitly Differentiable Reward Learning for Preference-based Reinforcement Learning Runze Liu, Fengshuo Bai, Yali Du, Yaodong Yang
Main Conference Track
One-shot Neural Backdoor Erasing via Adversarial Weight Masking Shuwen Chai, Jinghui Chen
Main Conference Track
Revisiting Neural Scaling Laws in Language and Vision Ibrahim M Alabdulmohsin, Behnam Neyshabur, Xiaohua Zhai
Main Conference Track
Efficient Phi-Regret Minimization in Extensive-Form Games via Online Mirror Descent Yu Bai, Chi Jin, Song Mei, Ziang Song, Tiancheng Yu
Main Conference Track
Long Range Graph Benchmark Vijay Prakash Dwivedi, Ladislav Rampášek, Michael Galkin, Ali Parviz, Guy Wolf, Anh Tuan Luu, Dominique Beaini
Datasets and Benchmarks Track
On the inability of Gaussian process regression to optimally learn compositional functions Matteo Giordano, Kolyan Ray, Johannes Schmidt-Hieber
Main Conference Track
Active Learning Through a Covering Lens Ofer Yehuda, Avihu Dekel, Guy Hacohen, Daphna Weinshall
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Uplifting Bandits Yu-Guan Hsieh, Shiva P. Kasiviswanathan, Branislav Kveton
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Training Uncertainty-Aware Classifiers with Conformalized Deep Learning Bat-Sheva Einbinder, Yaniv Romano, Matteo Sesia, Yanfei Zhou
Main Conference Track
A general approximation lower bound in $L^p$ norm, with applications to feed-forward neural networks El Mehdi Achour, Armand Foucault, Sébastien Gerchinovitz, François Malgouyres
Main Conference Track
EnvPool: A Highly Parallel Reinforcement Learning Environment Execution Engine Jiayi Weng, Min Lin, Shengyi Huang, Bo Liu, Denys Makoviichuk, Viktor Makoviychuk, Zichen Liu, Yufan Song, Ting Luo, Yukun Jiang, Zhongwen Xu, Shuicheng Yan
Datasets and Benchmarks Track
Generative Visual Prompt: Unifying Distributional Control of Pre-Trained Generative Models Chen Henry Wu, Saman Motamed, Shaunak Srivastava, Fernando D De la Torre
Main Conference Track
Implicit Warping for Animation with Image Sets Arun Mallya, Ting-Chun Wang, Ming-Yu Liu
Main Conference Track
FNeVR: Neural Volume Rendering for Face Animation Bohan Zeng, Boyu Liu, Hong Li, Xuhui Liu, Jianzhuang Liu, Dapeng Chen, Wei Peng, Baochang Zhang
Main Conference Track
Ontologue: Declarative Benchmark Construction for Ontological Multi-Label Classification Sean Yang, Bernease Herman, Bill Howe
Datasets and Benchmarks Track
Make an Omelette with Breaking Eggs: Zero-Shot Learning for Novel Attribute Synthesis Yu-Hsuan Li, Tzu-Yin Chao, Ching-Chun Huang, Pin-Yu Chen, Wei-Chen Chiu
Main Conference Track
Exploiting Semantic Relations for Glass Surface Detection Jiaying Lin, Yuen-Hei Yeung, Rynson Lau
Main Conference Track
Differentially Private Generalized Linear Models Revisited Raman Arora, Raef Bassily, Cristóbal Guzmán, Michael Menart, Enayat Ullah
Main Conference Track
GREED: A Neural Framework for Learning Graph Distance Functions Rishabh Ranjan, Siddharth Grover, Sourav Medya, Venkatesan Chakaravarthy, Yogish Sabharwal, Sayan Ranu
Main Conference Track
Domain Adaptation under Open Set Label Shift Saurabh Garg, Sivaraman Balakrishnan, Zachary Lipton
Main Conference Track
Efficient Adversarial Training without Attacking: Worst-Case-Aware Robust Reinforcement Learning Yongyuan Liang, Yanchao Sun, Ruijie Zheng, Furong Huang
Main Conference Track
Alleviating "Posterior Collapse'' in Deep Topic Models via Policy Gradient Yewen Li, Chaojie Wang, Zhibin Duan, Dongsheng Wang, Bo Chen, Bo An, Mingyuan Zhou
Main Conference Track
Tracking Functional Changes in Nonstationary Signals with Evolutionary Ensemble Bayesian Model for Robust Neural Decoding Xinyun Zhu, Yu Qi, Gang Pan, Yueming Wang
Main Conference Track
Zeroth-Order Hard-Thresholding: Gradient Error vs. Expansivity William de Vazelhes, Hualin Zhang, Huimin Wu, Xiaotong Yuan, Bin Gu
Main Conference Track
Collaborative Linear Bandits with Adversarial Agents: Near-Optimal Regret Bounds Aritra Mitra, Arman Adibi, George J. Pappas, Hamed Hassani
Main Conference Track
Differentially Private Graph Learning via Sensitivity-Bounded Personalized PageRank Alessandro Epasto, Vahab Mirrokni, Bryan Perozzi, Anton Tsitsulin, Peilin Zhong
Main Conference Track
How Well Do Unsupervised Learning Algorithms Model Human Real-time and Life-long Learning? Chengxu Zhuang, Ziyu Xiang, Yoon Bai, Xiaoxuan Jia, Nicholas Turk-Browne, Kenneth A. Norman, James J DiCarlo, Dan Yamins
Datasets and Benchmarks Track
Stochastic Multiple Target Sampling Gradient Descent Hoang Phan, Ngoc Tran, Trung Le, Toan Tran, Nhat Ho, Dinh Phung
Main Conference Track
Towards Out-of-Distribution Sequential Event Prediction: A Causal Treatment Chenxiao Yang, Qitian Wu, Qingsong Wen, Zhiqiang Zhou, Liang Sun, Junchi Yan
Main Conference Track
Hybrid Neural Autoencoders for Stimulus Encoding in Visual and Other Sensory Neuroprostheses Jacob Granley, Lucas Relic, Michael Beyeler
Main Conference Track
Tractable Function-Space Variational Inference in Bayesian Neural Networks Tim G. J. Rudner, Zonghao Chen, Yee Whye Teh, Yarin Gal
Main Conference Track
BMU-MoCo: Bidirectional Momentum Update for Continual Video-Language Modeling Yizhao Gao, Nanyi Fei, Haoyu Lu, Zhiwu Lu, Hao Jiang, Yijie Li, Zhao Cao
Main Conference Track
Can Hybrid Geometric Scattering Networks Help Solve the Maximum Clique Problem? Yimeng Min, Frederik Wenkel, Michael Perlmutter, Guy Wolf
Main Conference Track
Expected Improvement for Contextual Bandits Hung Tran-The, Sunil Gupta, Santu Rana, Tuan Truong, Long Tran-Thanh, Svetha Venkatesh
Main Conference Track
Redistribution of Weights and Activations for AdderNet Quantization Ying Nie, Kai Han, Haikang Diao, Chuanjian Liu, Enhua Wu, Yunhe Wang
Main Conference Track
Physically-Based Face Rendering for NIR-VIS Face Recognition Yunqi Miao, Alexandros Lattas, Jiankang Deng, Jungong Han, Stefanos Zafeiriou
Main Conference Track
DGraph: A Large-Scale Financial Dataset for Graph Anomaly Detection Xuanwen Huang, Yang Yang, Yang Wang, Chunping Wang, Zhisheng Zhang, Jiarong Xu, Lei Chen, Michalis Vazirgiannis
Datasets and Benchmarks Track
Globally Convergent Policy Search for Output Estimation Jack Umenberger, Max Simchowitz, Juan Perdomo, Kaiqing Zhang, Russ Tedrake
Main Conference Track
Escaping Saddle Points for Effective Generalization on Class-Imbalanced Data Harsh Rangwani, Sumukh K Aithal, Mayank Mishra, Venkatesh Babu R
Main Conference Track
Continuous Deep Q-Learning in Optimal Control Problems: Normalized Advantage Functions Analysis Anton Plaksin, Stepan Martyanov
Main Conference Track
Partial Identification of Treatment Effects with Implicit Generative Models Vahid Balazadeh Meresht, Vasilis Syrgkanis, Rahul G Krishnan
Main Conference Track
Robust Model Selection and Nearly-Proper Learning for GMMs Allen Liu, Jerry Li, Ankur Moitra
Main Conference Track
A2: Efficient Automated Attacker for Boosting Adversarial Training Zhuoer Xu, Guanghui Zhu, Changhua Meng, shiwen cui, Zhenzhe Ying, Weiqiang Wang, Ming GU, Yihua Huang
Main Conference Track
Shape, Light, and Material Decomposition from Images using Monte Carlo Rendering and Denoising Jon Hasselgren, Nikolai Hofmann, Jacob Munkberg
Main Conference Track
Convergence for score-based generative modeling with polynomial complexity Holden Lee, Jianfeng Lu, Yixin Tan
Main Conference Track
Kernel Interpolation with Sparse Grids Mohit Yadav, Daniel R. Sheldon, Cameron Musco
Main Conference Track
Contrastive Language-Image Pre-Training with Knowledge Graphs Xuran Pan, Tianzhu Ye, Dongchen Han, Shiji Song, Gao Huang
Main Conference Track
Reconstructing Training Data From Trained Neural Networks Niv Haim, Gal Vardi, Gilad Yehudai, Ohad Shamir, Michal Irani
Main Conference Track
Hierarchical Agglomerative Graph Clustering in Poly-Logarithmic Depth Laxman Dhulipala, David Eisenstat, Jakub Lacki, Vahab Mirrokni, Jessica Shi
Main Conference Track
On-Device Training Under 256KB Memory Ji Lin, Ligeng Zhu, Wei-Ming Chen, Wei-Chen Wang, Chuang Gan, Song Han
Main Conference Track
Behavior Transformers: Cloning $k$ modes with one stone Nur Muhammad Shafiullah, Zichen Cui, Ariuntuya (Arty) Altanzaya, Lerrel Pinto
Main Conference Track
Performative Power Moritz Hardt, Meena Jagadeesan, Celestine Mendler-Dünner
Main Conference Track
Diagonal State Spaces are as Effective as Structured State Spaces Ankit Gupta, Albert Gu, Jonathan Berant
Main Conference Track
Deep Fourier Up-Sampling man zhou, Hu Yu, Jie Huang, Feng Zhao, Jinwei Gu, Chen Change Loy, Deyu Meng, Chongyi Li
Main Conference Track
Generative Time Series Forecasting with Diffusion, Denoise, and Disentanglement Yan Li, Xinjiang Lu, Yaqing Wang, Dejing Dou
Main Conference Track
The Missing Invariance Principle found -- the Reciprocal Twin of Invariant Risk Minimization Dongsung Huh, Avinash Baidya
Main Conference Track
Signal Recovery with Non-Expansive Generative Network Priors Jorio Cocola
Main Conference Track
Towards Understanding the Mixture-of-Experts Layer in Deep Learning Zixiang Chen, Yihe Deng, Yue Wu, Quanquan Gu, Yuanzhi Li
Main Conference Track
Indicators of Attack Failure: Debugging and Improving Optimization of Adversarial Examples Maura Pintor, Luca Demetrio, Angelo Sotgiu, Ambra Demontis, Nicholas Carlini, Battista Biggio, Fabio Roli
Main Conference Track
Beyond accuracy: generalization properties of bio-plausible temporal credit assignment rules Yuhan Helena Liu, Arna Ghosh, Blake Richards, Eric Shea-Brown, Guillaume Lajoie
Main Conference Track
Parameter tuning and model selection in Optimal Transport with semi-dual Brenier formulation Adrien Vacher, Francois-Xavier Vialard
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VITA: Video Instance Segmentation via Object Token Association Miran Heo, Sukjun Hwang, Seoung Wug Oh, Joon-Young Lee, Seon Joo Kim
Main Conference Track
Bridging the Gap: Unifying the Training and Evaluation of Neural Network Binary Classifiers Nathan Tsoi, Kate Candon, Deyuan Li, Yofti Milkessa, Marynel Vázquez
Main Conference Track
Truncated proposals for scalable and hassle-free simulation-based inference Michael Deistler, Pedro J Goncalves, Jakob H Macke
Main Conference Track
When to Update Your Model: Constrained Model-based Reinforcement Learning Tianying Ji, Yu Luo, Fuchun Sun, Mingxuan Jing, Fengxiang He, Wenbing Huang
Main Conference Track
Noise Attention Learning: Enhancing Noise Robustness by Gradient Scaling Yangdi Lu, Yang Bo, Wenbo He
Main Conference Track
Iso-Dream: Isolating and Leveraging Noncontrollable Visual Dynamics in World Models Minting Pan, Xiangming Zhu, Yunbo Wang, Xiaokang Yang
Main Conference Track
PointNeXt: Revisiting PointNet++ with Improved Training and Scaling Strategies Guocheng Qian, Yuchen Li, Houwen Peng, Jinjie Mai, Hasan Hammoud, Mohamed Elhoseiny, Bernard Ghanem
Main Conference Track
Quantum Algorithms for Sampling Log-Concave Distributions and Estimating Normalizing Constants Andrew M. Childs, Tongyang Li, Jin-Peng Liu, Chunhao Wang, Ruizhe Zhang
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Physics-Embedded Neural Networks: Graph Neural PDE Solvers with Mixed Boundary Conditions Masanobu Horie, NAOTO MITSUME
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Mismatched No More: Joint Model-Policy Optimization for Model-Based RL Benjamin Eysenbach, Alexander Khazatsky, Sergey Levine, Ruslan Salakhutdinov
Main Conference Track
Phase diagram of Stochastic Gradient Descent in high-dimensional two-layer neural networks Rodrigo Veiga, Ludovic Stephan, Bruno Loureiro, Florent Krzakala, Lenka Zdeborová
Main Conference Track
Constrained Stochastic Nonconvex Optimization with State-dependent Markov Data Abhishek Roy, Krishnakumar Balasubramanian, Saeed Ghadimi
Main Conference Track
Adapting Self-Supervised Vision Transformers by Probing Attention-Conditioned Masking Consistency Viraj Prabhu, Sriram Yenamandra, Aaditya Singh, Judy Hoffman
Main Conference Track
MaskTune: Mitigating Spurious Correlations by Forcing to Explore Saeid Asgari, Aliasghar Khani, Fereshte Khani, Ali Gholami, Linh Tran, Ali Mahdavi Amiri, Ghassan Hamarneh
Main Conference Track
A Dataset for Efforts Towards Achieving the Sustainable Development Goal of Safe Working Environments Eirik Lund Flogard, Ole Jakob Mengshoel
Datasets and Benchmarks Track
Decomposing NeRF for Editing via Feature Field Distillation Sosuke Kobayashi, Eiichi Matsumoto, Vincent Sitzmann
Main Conference Track
Sample-Then-Optimize Batch Neural Thompson Sampling Zhongxiang Dai, YAO SHU, Bryan Kian Hsiang Low, Patrick Jaillet
Main Conference Track
Video-based Human-Object Interaction Detection from Tubelet Tokens Danyang Tu, Wei Sun, Xiongkuo Min, Guangtao Zhai, Wei Shen
Main Conference Track
Efficient and Stable Fully Dynamic Facility Location Sayan Bhattacharya, Silvio Lattanzi, Nikos Parotsidis
Main Conference Track
MCVD - Masked Conditional Video Diffusion for Prediction, Generation, and Interpolation Vikram Voleti, Alexia Jolicoeur-Martineau, Chris Pal
Main Conference Track
Addressing Leakage in Concept Bottleneck Models Marton Havasi, Sonali Parbhoo, Finale Doshi-Velez
Main Conference Track
Adaptive Oracle-Efficient Online Learning Guanghui Wang, Zihao Hu, Vidya Muthukumar, Jacob D. Abernethy
Main Conference Track
MoVQ: Modulating Quantized Vectors for High-Fidelity Image Generation Chuanxia Zheng, Tung-Long Vuong, Jianfei Cai, Dinh Phung
Main Conference Track
Meta-Auto-Decoder for Solving Parametric Partial Differential Equations Xiang Huang, Zhanhong Ye, Hongsheng Liu, Shi Ji, Zidong Wang, Kang Yang, Yang Li, Min Wang, Haotian CHU, Fan Yu, Bei Hua, Lei Chen, Bin Dong
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Sharpness-Aware Training for Free JIAWEI DU, Daquan Zhou, Jiashi Feng, Vincent Tan, Joey Tianyi Zhou
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Generalization Error Bounds on Deep Learning with Markov Datasets Lan V. Truong
Main Conference Track
AirfRANS: High Fidelity Computational Fluid Dynamics Dataset for Approximating Reynolds-Averaged Navier–Stokes Solutions Florent Bonnet, Jocelyn Mazari, Paola Cinnella, Patrick Gallinari
Datasets and Benchmarks Track
Generalization for multiclass classification with overparameterized linear models Vignesh Subramanian, Rahul Arya, Anant Sahai
Main Conference Track
Inception Transformer Chenyang Si, Weihao Yu, Pan Zhou, Yichen Zhou, Xinchao Wang, Shuicheng Yan
Main Conference Track
ElasticMVS: Learning elastic part representation for self-supervised multi-view stereopsis Jinzhi Zhang, Ruofan Tang, Zheng Cao, Jing Xiao, Ruqi Huang, LU FANG
Main Conference Track
Adaptive Stochastic Variance Reduction for Non-convex Finite-Sum Minimization Ali Kavis, Stratis Skoulakis, Kimon Antonakopoulos, Leello Tadesse Dadi, Volkan Cevher
Main Conference Track
Thinking Outside the Ball: Optimal Learning with Gradient Descent for Generalized Linear Stochastic Convex Optimization Idan Amir, Roi Livni, Nati Srebro
Main Conference Track
Generalization Properties of NAS under Activation and Skip Connection Search Zhenyu Zhu, Fanghui Liu, Grigorios Chrysos, Volkan Cevher
Main Conference Track
Mesoscopic modeling of hidden spiking neurons Shuqi Wang, Valentin Schmutz, Guillaume Bellec, Wulfram Gerstner
Main Conference Track
SageMix: Saliency-Guided Mixup for Point Clouds Sanghyeok Lee, Minkyu Jeon, Injae Kim, Yunyang Xiong, Hyunwoo J Kim
Main Conference Track
Denoising Diffusion Restoration Models Bahjat Kawar, Michael Elad, Stefano Ermon, Jiaming Song
Main Conference Track
On Translation and Reconstruction Guarantees of the Cycle-Consistent Generative Adversarial Networks Anish Chakrabarty, Swagatam Das
Main Conference Track
Adversarial Training with Complementary Labels: On the Benefit of Gradually Informative Attacks Jianan Zhou, Jianing Zhu, Jingfeng ZHANG, Tongliang Liu, Gang Niu, Bo Han, Masashi Sugiyama
Main Conference Track
Tractable Optimality in Episodic Latent MABs Jeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor
Main Conference Track
A Characterization of Semi-Supervised Adversarially Robust PAC Learnability Idan Attias, Steve Hanneke, Yishay Mansour
Main Conference Track
Data-IQ: Characterizing subgroups with heterogeneous outcomes in tabular data Nabeel Seedat, Jonathan Crabbé, Ioana Bica, Mihaela van der Schaar
Main Conference Track
Task-Free Continual Learning via Online Discrepancy Distance Learning Fei Ye, Adrian G. Bors
Main Conference Track
BinauralGrad: A Two-Stage Conditional Diffusion Probabilistic Model for Binaural Audio Synthesis Yichong Leng, Zehua Chen, Junliang Guo, Haohe Liu, Jiawei Chen, Xu Tan, Danilo P. Mandic, Lei He, Xiangyang Li, Tao Qin, sheng zhao, Tie-Yan Liu
Main Conference Track
ConfLab: A Data Collection Concept, Dataset, and Benchmark for Machine Analysis of Free-Standing Social Interactions in the Wild Chirag Raman, Jose Vargas Quiros, Stephanie Tan, Ashraful Islam, Ekin Gedik, Hayley Hung
Datasets and Benchmarks Track
Flamingo: a Visual Language Model for Few-Shot Learning Jean-Baptiste Alayrac, Jeff Donahue, Pauline Luc, Antoine Miech, Iain Barr, Yana Hasson, Karel Lenc, Arthur Mensch, Katherine Millican, Malcolm Reynolds, Roman Ring, Eliza Rutherford, Serkan Cabi, Tengda Han, Zhitao Gong, Sina Samangooei, Marianne Monteiro, Jacob L Menick, Sebastian Borgeaud, Andy Brock, Aida Nematzadeh, Sahand Sharifzadeh, Mikołaj Bińkowski, Ricardo Barreira, Oriol Vinyals, Andrew Zisserman, Karén Simonyan
Main Conference Track
Understanding the Eluder Dimension Gene Li, Pritish Kamath, Dylan J Foster, Nati Srebro
Main Conference Track
Predictive Querying for Autoregressive Neural Sequence Models Alex Boyd, Samuel Showalter, Stephan Mandt, Padhraic Smyth
Main Conference Track
Learning State-Aware Visual Representations from Audible Interactions Himangi Mittal, Pedro Morgado, Unnat Jain, Abhinav Gupta
Main Conference Track
Context-Based Dynamic Pricing with Partially Linear Demand Model Jinzhi Bu, David Simchi-Levi, Chonghuan Wang
Main Conference Track
NeuroSchedule: A Novel Effective GNN-based Scheduling Method for High-level Synthesis Jun Zeng, Mingyang Kou, Hailong Yao
Main Conference Track
Hand-Object Interaction Image Generation Hezhen Hu, Weilun Wang, Wengang Zhou, Houqiang Li
Main Conference Track
DISCO: Adversarial Defense with Local Implicit Functions Chih-Hui Ho, Nuno Vasconcelos
Main Conference Track
Distinguishing discrete and continuous behavioral variability using warped autoregressive HMMs Julia Costacurta, Lea Duncker, Blue Sheffer, Winthrop Gillis, Caleb Weinreb, Jeffrey Markowitz, Sandeep R Datta, Alex Williams, Scott Linderman
Main Conference Track
RORL: Robust Offline Reinforcement Learning via Conservative Smoothing Rui Yang, Chenjia Bai, Xiaoteng Ma, Zhaoran Wang, Chongjie Zhang, Lei Han
Main Conference Track
Optimal Scaling for Locally Balanced Proposals in Discrete Spaces Haoran Sun, Hanjun Dai, Dale Schuurmans
Main Conference Track
The Impact of Task Underspecification in Evaluating Deep Reinforcement Learning Vindula Jayawardana, Catherine Tang, Sirui Li, Dajiang Suo, Cathy Wu
Main Conference Track
Zero-Shot 3D Drug Design by Sketching and Generating Siyu Long, Yi Zhou, Xinyu Dai, Hao Zhou
Main Conference Track
Decoupling Knowledge from Memorization: Retrieval-augmented Prompt Learning Xiang Chen, Lei Li, Ningyu Zhang, Xiaozhuan Liang, Shumin Deng, Chuanqi Tan, Fei Huang, Luo Si, Huajun Chen
Main Conference Track
Polynomial time guarantees for the Burer-Monteiro method Diego Cifuentes, Ankur Moitra
Main Conference Track
Optimal Comparator Adaptive Online Learning with Switching Cost Zhiyu Zhang, Ashok Cutkosky, Yannis Paschalidis
Main Conference Track
A Robust Phased Elimination Algorithm for Corruption-Tolerant Gaussian Process Bandits Ilija Bogunovic, Zihan Li, Andreas Krause, Jonathan Scarlett
Main Conference Track
Fair Rank Aggregation Diptarka Chakraborty, Syamantak Das, Arindam Khan, Aditya Subramanian
Main Conference Track
Beyond IID: data-driven decision-making in heterogeneous environments Omar Besbes, Will Ma, Omar Mouchtaki
Main Conference Track
Neur2SP: Neural Two-Stage Stochastic Programming Rahul Mihir Patel, Justin Dumouchelle, Elias Khalil, Merve Bodur
Main Conference Track
SQ Lower Bounds for Learning Single Neurons with Massart Noise Ilias Diakonikolas, Daniel Kane, Lisheng Ren, Yuxin Sun
Main Conference Track
MaskPlace: Fast Chip Placement via Reinforced Visual Representation Learning Yao Lai, Yao Mu, Ping Luo
Main Conference Track
List-Decodable Sparse Mean Estimation Shiwei Zeng, Jie Shen
Main Conference Track
Structure-Aware Image Segmentation with Homotopy Warping Xiaoling Hu
Main Conference Track
Positive-Unlabeled Learning using Random Forests via Recursive Greedy Risk Minimization Jonathan Wilton, Abigail Koay, Ryan Ko, Miao Xu, Nan Ye
Main Conference Track
Extracting computational mechanisms from neural data using low-rank RNNs Adrian Valente, Jonathan W Pillow, Srdjan Ostojic
Main Conference Track
Pluralistic Image Completion with Gaussian Mixture Models Xiaobo Xia, Wenhao Yang, Jie Ren, Yewen Li, Yibing Zhan, Bo Han, Tongliang Liu
Main Conference Track
A Fast Post-Training Pruning Framework for Transformers Woosuk Kwon, Sehoon Kim, Michael W. Mahoney, Joseph Hassoun, Kurt Keutzer, Amir Gholami
Main Conference Track
SurDis: A Surface Discontinuity Dataset for Wearable Technology to Assist Blind Navigation in Urban Environments Kuan Yew Leong, Siew Mooi Lim
Datasets and Benchmarks Track
Interventions, Where and How? Experimental Design for Causal Models at Scale Panagiotis Tigas, Yashas Annadani, Andrew Jesson, Bernhard Schölkopf, Yarin Gal, Stefan Bauer
Main Conference Track
Dual-discriminative Graph Neural Network for Imbalanced Graph-level Anomaly Detection GE ZHANG, Zhenyu Yang, Jia Wu, Jian Yang, Shan Xue, Hao Peng, Jianlin Su, Chuan Zhou, Quan Z. Sheng, Leman Akoglu, Charu Aggarwal
Main Conference Track
Posted Pricing and Dynamic Prior-independent Mechanisms with Value Maximizers Yuan Deng, Vahab Mirrokni, Hanrui Zhang
Main Conference Track
Curious Exploration via Structured World Models Yields Zero-Shot Object Manipulation Cansu Sancaktar, Sebastian Blaes, Georg Martius
Main Conference Track
Estimating Noise Transition Matrix with Label Correlations for Noisy Multi-Label Learning Shikun Li, Xiaobo Xia, Hansong Zhang, Yibing Zhan, Shiming Ge, Tongliang Liu
Main Conference Track
Active Learning Polynomial Threshold Functions Omri Ben-Eliezer, Max Hopkins, Chutong Yang, Hantao Yu
Main Conference Track
Single-phase deep learning in cortico-cortical networks Will Greedy, Heng Wei Zhu, Joseph Pemberton, Jack Mellor, Rui Ponte Costa
Main Conference Track
Domain Generalization by Learning and Removing Domain-specific Features Yu Ding, Lei Wang, Bin Liang, Shuming Liang, Yang Wang, Fang Chen
Main Conference Track
Torsional Diffusion for Molecular Conformer Generation Bowen Jing, Gabriele Corso, Jeffrey Chang, Regina Barzilay, Tommi Jaakkola
Main Conference Track
LiteTransformerSearch: Training-free Neural Architecture Search for Efficient Language Models Mojan Javaheripi, Gustavo de Rosa, Subhabrata Mukherjee, Shital Shah, Tomasz Religa, Caio Cesar Teodoro Mendes, Sebastien Bubeck, Farinaz Koushanfar, Debadeepta Dey
Main Conference Track
AgraSSt: Approximate Graph Stein Statistics for Interpretable Assessment of Implicit Graph Generators Wenkai Xu, Gesine D Reinert
Main Conference Track
On the Limitations of Stochastic Pre-processing Defenses Yue Gao, I Shumailov, Kassem Fawaz, Nicolas Papernot
Main Conference Track
Iterative Scene Graph Generation Siddhesh Khandelwal, Leonid Sigal
Main Conference Track
Proximal Point Imitation Learning Luca Viano, Angeliki Kamoutsi, Gergely Neu, Igor Krawczuk, Volkan Cevher
Main Conference Track
Heatmap Distribution Matching for Human Pose Estimation Haoxuan Qu, Li Xu, Yujun Cai, Lin Geng Foo, Jun Liu
Main Conference Track
Mining Unseen Classes via Regional Objectness: A Simple Baseline for Incremental Segmentation Zekang Zhang, Guangyu Gao, Zhiyuan Fang, Jianbo Jiao, Yunchao Wei
Main Conference Track
Bezier Gaussian Processes for Tall and Wide Data Martin Jørgensen, Michael A Osborne
Main Conference Track
Smoothed Embeddings for Certified Few-Shot Learning Mikhail Pautov, Olesya Kuznetsova, Nurislam Tursynbek, Aleksandr Petiushko, Ivan Oseledets
Main Conference Track
Finite Sample Analysis Of Dynamic Regression Parameter Learning Mark Kozdoba, Edward Moroshko, Shie Mannor, Yacov Crammer
Main Conference Track
Group Meritocratic Fairness in Linear Contextual Bandits Riccardo Grazzi, Arya Akhavan, John IF Falk, Leonardo Cella, Massimiliano Pontil
Main Conference Track
New Lower Bounds for Private Estimation and a Generalized Fingerprinting Lemma Gautam Kamath, Argyris Mouzakis, Vikrant Singhal
Main Conference Track
Lower Bounds on Randomly Preconditioned Lasso via Robust Sparse Designs Jonathan Kelner, Frederic Koehler, Raghu Meka, Dhruv Rohatgi
Main Conference Track
Model-based Safe Deep Reinforcement Learning via a Constrained Proximal Policy Optimization Algorithm Ashish K Jayant, Shalabh Bhatnagar
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Exact Solutions of a Deep Linear Network Liu Ziyin, Botao Li, Xiangming Meng
Main Conference Track
An Adaptive Kernel Approach to Federated Learning of Heterogeneous Causal Effects Thanh Vinh Vo, Arnab Bhattacharyya, Young Lee, Tze-Yun Leong
Main Conference Track
FeLMi : Few shot Learning with hard Mixup Aniket Roy, Anshul Shah, Ketul Shah, Prithviraj Dhar, Anoop Cherian, Rama Chellappa
Main Conference Track
EpiGRAF: Rethinking training of 3D GANs Ivan Skorokhodov, Sergey Tulyakov, Yiqun Wang, Peter Wonka
Main Conference Track
Towards Trustworthy Automatic Diagnosis Systems by Emulating Doctors' Reasoning with Deep Reinforcement Learning Arsene Fansi Tchango, Rishab Goel, Julien Martel, Zhi Wen, Gaetan Marceau Caron, Joumana Ghosn
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Towards Improving Faithfulness in Abstractive Summarization Xiuying Chen, Mingzhe Li, Xin Gao, Xiangliang Zhang
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ZIN: When and How to Learn Invariance Without Environment Partition? Yong Lin, Shengyu Zhu, Lu Tan, Peng Cui
Main Conference Track
Random Sharpness-Aware Minimization Yong Liu, Siqi Mai, Minhao Cheng, Xiangning Chen, Cho-Jui Hsieh, Yang You
Main Conference Track
Active Surrogate Estimators: An Active Learning Approach to Label-Efficient Model Evaluation Jannik Kossen, Sebastian Farquhar, Yarin Gal, Thomas Rainforth
Main Conference Track
HAPI: A Large-scale Longitudinal Dataset of Commercial ML API Predictions Lingjiao Chen, Zhihua Jin, Evan Sabri Eyuboglu, Christopher Ré, Matei Zaharia, James Y Zou
Datasets and Benchmarks Track
Near-Optimal Regret Bounds for Multi-batch Reinforcement Learning Zihan Zhang, Yuhang Jiang, Yuan Zhou, Xiangyang Ji
Main Conference Track
OST: Improving Generalization of DeepFake Detection via One-Shot Test-Time Training Liang Chen, Yong Zhang, Yibing Song, Jue Wang, Lingqiao Liu
Main Conference Track
The Surprising Effectiveness of PPO in Cooperative Multi-Agent Games Chao Yu, Akash Velu, Eugene Vinitsky, Jiaxuan Gao, Yu Wang, Alexandre Bayen, YI WU
Datasets and Benchmarks Track
Resolving the data ambiguity for periodic crystals Daniel Widdowson, Vitaliy Kurlin
Main Conference Track
Video PreTraining (VPT): Learning to Act by Watching Unlabeled Online Videos Bowen Baker, Ilge Akkaya, Peter Zhokov, Joost Huizinga, Jie Tang, Adrien Ecoffet, Brandon Houghton, Raul Sampedro, Jeff Clune
Main Conference Track
GLOBEM Dataset: Multi-Year Datasets for Longitudinal Human Behavior Modeling Generalization Xuhai Xu, Han Zhang, Yasaman Sefidgar, Yiyi Ren, Xin Liu, Woosuk Seo, Jennifer Brown, Kevin Kuehn, Mike Merrill, Paula Nurius, Shwetak Patel, Tim Althoff, Margaret Morris, Eve Riskin, Jennifer Mankoff, Anind Dey
Datasets and Benchmarks Track
Shape And Structure Preserving Differential Privacy Carlos Soto, Karthik Bharath, Matthew Reimherr, Aleksandra Slavković
Main Conference Track
Transformers meet Stochastic Block Models: Attention with Data-Adaptive Sparsity and Cost Sungjun Cho, Seonwoo Min, Jinwoo Kim, Moontae Lee, Honglak Lee, Seunghoon Hong
Main Conference Track
Characteristics of Harmful Text: Towards Rigorous Benchmarking of Language Models Maribeth Rauh, John Mellor, Jonathan Uesato, Po-Sen Huang, Johannes Welbl, Laura Weidinger, Sumanth Dathathri, Amelia Glaese, Geoffrey Irving, Iason Gabriel, William Isaac, Lisa Anne Hendricks
Datasets and Benchmarks Track
APG: Adaptive Parameter Generation Network for Click-Through Rate Prediction Bencheng Yan, Pengjie Wang, Kai Zhang, Feng Li, Hongbo Deng, Jian Xu, Bo Zheng
Main Conference Track
NeoRL: A Near Real-World Benchmark for Offline Reinforcement Learning Rong-Jun Qin, Xingyuan Zhang, Songyi Gao, Xiong-Hui Chen, Zewen Li, Weinan Zhang, Yang Yu
Datasets and Benchmarks Track
Stochastic Halpern Iteration with Variance Reduction for Stochastic Monotone Inclusions Xufeng Cai, Chaobing Song, Cristóbal Guzmán, Jelena Diakonikolas
Main Conference Track
SNN-RAT: Robustness-enhanced Spiking Neural Network through Regularized Adversarial Training Jianhao Ding, Tong Bu, Zhaofei Yu, Tiejun Huang, Jian Liu
Main Conference Track
The Mechanism of Prediction Head in Non-contrastive Self-supervised Learning Zixin Wen, Yuanzhi Li
Main Conference Track
Counterfactual Temporal Point Processes Kimia Noorbakhsh, Manuel Rodriguez
Main Conference Track
Chain-of-Thought Prompting Elicits Reasoning in Large Language Models Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, brian ichter, Fei Xia, Ed Chi, Quoc V Le, Denny Zhou
Main Conference Track
House of Cans: Covert Transmission of Internal Datasets via Capacity-Aware Neuron Steganography Xudong Pan, Shengyao Zhang, Mi Zhang, Yifan Yan, Min Yang
Main Conference Track
Polynomial-Time Optimal Equilibria with a Mediator in Extensive-Form Games Brian Zhang, Tuomas Sandholm
Main Conference Track
Dungeons and Data: A Large-Scale NetHack Dataset Eric Hambro, Roberta Raileanu, Danielle Rothermel, Vegard Mella, Tim Rocktäschel, Heinrich Küttler, Naila Murray
Datasets and Benchmarks Track
Optimal Dynamic Regret in LQR Control Dheeraj Baby, Yu-Xiang Wang
Main Conference Track
Gradient Descent Is Optimal Under Lower Restricted Secant Inequality And Upper Error Bound Charles Guille-Escuret, Adam Ibrahim, Baptiste Goujaud, Ioannis Mitliagkas
Main Conference Track
GenSDF: Two-Stage Learning of Generalizable Signed Distance Functions Gene Chou, Ilya Chugunov, Felix Heide
Main Conference Track
Forecasting Human Trajectory from Scene History Mancheng Meng, Ziyan Wu, Terrence Chen, Xiran Cai, Xiang Zhou, Fan Yang, Dinggang Shen
Main Conference Track
Debiasing Graph Neural Networks via Learning Disentangled Causal Substructure Shaohua Fan, Xiao Wang, Yanhu Mo, Chuan Shi, Jian Tang
Main Conference Track
Stochastic Online Learning with Feedback Graphs: Finite-Time and Asymptotic Optimality Teodor Vanislavov Marinov, Mehryar Mohri, Julian Zimmert
Main Conference Track
Asymptotics of $\ell_2$ Regularized Network Embeddings Andrew Davison
Main Conference Track
Differentiable hierarchical and surrogate gradient search for spiking neural networks Kaiwei Che, Luziwei Leng, Kaixuan Zhang, Jianguo Zhang, Qinghu Meng, Jie Cheng, Qinghai Guo, Jianxing Liao
Main Conference Track
On Embeddings for Numerical Features in Tabular Deep Learning Yury Gorishniy, Ivan Rubachev, Artem Babenko
Main Conference Track
Visual Prompting via Image Inpainting Amir Bar, Yossi Gandelsman, Trevor Darrell, Amir Globerson, Alexei Efros
Main Conference Track
MonoSDF: Exploring Monocular Geometric Cues for Neural Implicit Surface Reconstruction Zehao Yu, Songyou Peng, Michael Niemeyer, Torsten Sattler, Andreas Geiger
Main Conference Track
OpenAUC: Towards AUC-Oriented Open-Set Recognition Zitai Wang, Qianqian Xu, Zhiyong Yang, Yuan He, Xiaochun Cao, Qingming Huang
Main Conference Track
Reduction Algorithms for Persistence Diagrams of Networks: CoralTDA and PrunIT Cuneyt G Akcora, Murat Kantarcioglu, Yulia Gel, Baris Coskunuzer
Main Conference Track
TreeMoCo: Contrastive Neuron Morphology Representation Learning Hanbo Chen, Jiawei Yang, Daniel Iascone, Lijuan Liu, Lei He, Hanchuan Peng, Jianhua Yao
Main Conference Track
Compositional Generalization in Unsupervised Compositional Representation Learning: A Study on Disentanglement and Emergent Language Zhenlin Xu, Marc Niethammer, Colin A Raffel
Main Conference Track
Improving Zero-Shot Generalization in Offline Reinforcement Learning using Generalized Similarity Functions Bogdan Mazoure, Ilya Kostrikov, Ofir Nachum, Jonathan J Tompson
Main Conference Track
GAUDI: A Neural Architect for Immersive 3D Scene Generation Miguel Angel Bautista, Pengsheng Guo, Samira Abnar, Walter Talbott, Alexander Toshev, Zhuoyuan Chen, Laurent Dinh, Shuangfei Zhai, Hanlin Goh, Daniel Ulbricht, Afshin Dehghan, Joshua Susskind
Main Conference Track
Mask-based Latent Reconstruction for Reinforcement Learning Tao Yu, Zhizheng Zhang, Cuiling Lan, Yan Lu, Zhibo Chen
Main Conference Track
Product Ranking for Revenue Maximization with Multiple Purchases Renzhe Xu, Xingxuan Zhang, Bo Li, Yafeng Zhang, Xiaolong Chen, Peng Cui
Main Conference Track
One Model to Edit Them All: Free-Form Text-Driven Image Manipulation with Semantic Modulations Yiming Zhu, Hongyu Liu, Yibing Song, Ziyang Yuan, Xintong Han, Chun Yuan, Qifeng Chen, Jue Wang
Main Conference Track
Luckiness in Multiscale Online Learning Wouter M. Koolen, Muriel F. Pérez-Ortiz
Main Conference Track
Deep Active Learning by Leveraging Training Dynamics Haonan Wang, Wei Huang, Ziwei Wu, Hanghang Tong, Andrew J Margenot, Jingrui He
Main Conference Track
Learning and Covering Sums of Independent Random Variables with Unbounded Support Alkis Kalavasis, Konstantinos Stavropoulos, Emmanouil Zampetakis
Main Conference Track
LGDN: Language-Guided Denoising Network for Video-Language Modeling Haoyu Lu, Mingyu Ding, Nanyi Fei, Yuqi Huo, Zhiwu Lu
Main Conference Track
LieGG: Studying Learned Lie Group Generators Artem Moskalev, Anna Sepliarskaia, Ivan Sosnovik, Arnold Smeulders
Main Conference Track
FourierNets enable the design of highly non-local optical encoders for computational imaging Diptodip Deb, Zhenfei Jiao, Ruth Sims, Alex Chen, Michael Broxton, Misha B Ahrens, Kaspar Podgorski, Srinivas C Turaga
Main Conference Track
Benign Overfitting in Two-layer Convolutional Neural Networks Yuan Cao, Zixiang Chen, Misha Belkin, Quanquan Gu
Main Conference Track
Discovery of Single Independent Latent Variable Uri Shaham, Jonathan Svirsky, Ori Katz, Ronen Talmon
Main Conference Track
Meta-ticket: Finding optimal subnetworks for few-shot learning within randomly initialized neural networks Daiki Chijiwa, Shin'ya Yamaguchi, Atsutoshi Kumagai, Yasutoshi Ida
Main Conference Track
LAION-5B: An open large-scale dataset for training next generation image-text models Christoph Schuhmann, Romain Beaumont, Richard Vencu, Cade Gordon, Ross Wightman, Mehdi Cherti, Theo Coombes, Aarush Katta, Clayton Mullis, Mitchell Wortsman, Patrick Schramowski, Srivatsa Kundurthy, Katherine Crowson, Ludwig Schmidt, Robert Kaczmarczyk, Jenia Jitsev
Datasets and Benchmarks Track
Constants of motion network Muhammad Firmansyah Kasim, Yi Heng Lim
Main Conference Track
HUMUS-Net: Hybrid Unrolled Multi-scale Network Architecture for Accelerated MRI Reconstruction Zalan Fabian, Berk Tinaz, Mahdi Soltanolkotabi
Main Conference Track
A Damped Newton Method Achieves Global $\mathcal O \left(\frac{1}{k^2}\right)$ and Local Quadratic Convergence Rate Slavomír Hanzely, Dmitry Kamzolov, Dmitry Pasechnyuk, Alexander Gasnikov, Peter Richtarik, Martin Takac
Main Conference Track
Disentangling the Predictive Variance of Deep Ensembles through the Neural Tangent Kernel Seijin Kobayashi, Pau Vilimelis Aceituno, Johannes von Oswald
Main Conference Track
High-dimensional limit theorems for SGD: Effective dynamics and critical scaling Gerard Ben Arous, Reza Gheissari, Aukosh Jagannath
Main Conference Track
Online Deep Equilibrium Learning for Regularization by Denoising Jiaming Liu, Xiaojian Xu, Weijie Gan, shirin shoushtari, Ulugbek Kamilov
Main Conference Track
Semantic Exploration from Language Abstractions and Pretrained Representations Allison Tam, Neil Rabinowitz, Andrew Lampinen, Nicholas A. Roy, Stephanie Chan, DJ Strouse, Jane Wang, Andrea Banino, Felix Hill
Main Conference Track
Earthformer: Exploring Space-Time Transformers for Earth System Forecasting Zhihan Gao, Xingjian Shi, Hao Wang, Yi Zhu, Yuyang (Bernie) Wang, Mu Li, Dit-Yan Yeung
Main Conference Track
Benchopt: Reproducible, efficient and collaborative optimization benchmarks Thomas Moreau, Mathurin Massias, Alexandre Gramfort, Pierre Ablin, Pierre-Antoine Bannier, Benjamin Charlier, Mathieu Dagréou, Tom Dupre la Tour, Ghislain DURIF, Cassio F. Dantas, Quentin Klopfenstein, Johan Larsson, En Lai, Tanguy Lefort, Benoît Malézieux, Badr MOUFAD, Binh T. Nguyen, Alain Rakotomamonjy, Zaccharie Ramzi, Joseph Salmon, Samuel Vaiter
Main Conference Track
SketchBoost: Fast Gradient Boosted Decision Tree for Multioutput Problems Leonid Iosipoi, Anton Vakhrushev
Main Conference Track
Deep Attentive Belief Propagation: Integrating Reasoning and Learning for Solving Constraint Optimization Problems Yanchen Deng, Shufeng Kong, Caihua Liu, Bo An
Main Conference Track
Conservative Dual Policy Optimization for Efficient Model-Based Reinforcement Learning Shenao Zhang
Main Conference Track
Decentralized Training of Foundation Models in Heterogeneous Environments Binhang Yuan, Yongjun He, Jared Davis, Tianyi Zhang, Tri Dao, Beidi Chen, Percy Liang, Christopher Ré, Ce Zhang
Main Conference Track
Cross Aggregation Transformer for Image Restoration Zheng Chen, Yulun Zhang, Jinjin Gu, yongbing zhang, Linghe Kong, Xin Yuan
Main Conference Track
Neural Payoff Machines: Predicting Fair and Stable Payoff Allocations Among Team Members Daphne Cornelisse, Thomas Rood, Yoram Bachrach, Mateusz Malinowski, Tal Kachman
Main Conference Track
Learning Recourse on Instance Environment to Enhance Prediction Accuracy Lokesh N, Guntakanti Sai Koushik, Abir De, Sunita Sarawagi
Main Conference Track
Learning to Re-weight Examples with Optimal Transport for Imbalanced Classification Dandan Guo, Zhuo Li, meixi zheng, He Zhao, Mingyuan Zhou, Hongyuan Zha
Main Conference Track
DIMES: A Differentiable Meta Solver for Combinatorial Optimization Problems Ruizhong Qiu, Zhiqing Sun, Yiming Yang
Main Conference Track
Confident Approximate Policy Iteration for Efficient Local Planning in $q^\pi$-realizable MDPs Gellért Weisz, András György, Tadashi Kozuno, Csaba Szepesvari
Main Conference Track
Finding Correlated Equilibrium of Constrained Markov Game: A Primal-Dual Approach Ziyi Chen, Shaocong Ma, Yi Zhou
Main Conference Track
NSNet: A General Neural Probabilistic Framework for Satisfiability Problems Zhaoyu Li, Xujie Si
Main Conference Track
Brain Network Transformer Xuan Kan, Wei Dai, Hejie Cui, Zilong Zhang, Ying Guo, Carl Yang
Main Conference Track
A Neural Corpus Indexer for Document Retrieval Yujing Wang, Yingyan Hou, Haonan Wang, Ziming Miao, Shibin Wu, Qi Chen, Yuqing Xia, Chengmin Chi, Guoshuai Zhao, Zheng Liu, Xing Xie, Hao Sun, Weiwei Deng, Qi Zhang, Mao Yang
Main Conference Track
Perfect Sampling from Pairwise Comparisons Dimitris Fotakis, Alkis Kalavasis, Christos Tzamos
Main Conference Track
Improved Utility Analysis of Private CountSketch Rasmus Pagh, Mikkel Thorup
Main Conference Track
Optimal Efficiency-Envy Trade-Off via Optimal Transport Steven Yin, Christian Kroer
Main Conference Track
Non-Linear Coordination Graphs Yipeng Kang, Tonghan Wang, Qianlan Yang, Xiaoran Wu, Chongjie Zhang
Main Conference Track
SafeBench: A Benchmarking Platform for Safety Evaluation of Autonomous Vehicles Chejian Xu, Wenhao Ding, Weijie Lyu, ZUXIN LIU, Shuai Wang, Yihan He, Hanjiang Hu, DING ZHAO, Bo Li
Datasets and Benchmarks Track
Improving Diffusion Models for Inverse Problems using Manifold Constraints Hyungjin Chung, Byeongsu Sim, Dohoon Ryu, Jong Chul Ye
Main Conference Track
Semi-supervised Vision Transformers at Scale Zhaowei Cai, Avinash Ravichandran, Paolo Favaro, Manchen Wang, Davide Modolo, Rahul Bhotika, Zhuowen Tu, Stefano Soatto
Main Conference Track
Fast Bayesian Estimation of Point Process Intensity as Function of Covariates Hideaki Kim, Taichi Asami, Hiroyuki Toda
Main Conference Track
Online PAC-Bayes Learning Maxime Haddouche, Benjamin Guedj
Main Conference Track
Deep Model Reassembly Xingyi Yang, Daquan Zhou, Songhua Liu, Jingwen Ye, Xinchao Wang
Main Conference Track
Fast Algorithms for Packing Proportional Fairness and its Dual Francisco Criado, David Martinez-Rubio, Sebastian Pokutta
Main Conference Track
A Closer Look at Prototype Classifier for Few-shot Image Classification Mingcheng Hou, Issei Sato
Main Conference Track
When are Offline Two-Player Zero-Sum Markov Games Solvable? Qiwen Cui, Simon S Du
Main Conference Track
BigBio: A Framework for Data-Centric Biomedical Natural Language Processing Jason Fries, Leon Weber, Natasha Seelam, Gabriel Altay, Debajyoti Datta, Samuele Garda, Sunny Kang, Rosaline Su, Wojciech Kusa, Samuel Cahyawijaya, Fabio Barth, Simon Ott, Matthias Samwald, Stephen Bach, Stella Biderman, Mario Sänger, Bo Wang, Alison Callahan, Daniel León Periñán, Théo Gigant, Patrick Haller, Jenny Chim, Jose Posada, John Giorgi, Karthik Rangasai Sivaraman, Marc Pàmies, Marianna Nezhurina, Robert Martin, Michael Cullan, Moritz Freidank, Nathan Dahlberg, Shubhanshu Mishra, Shamik Bose, Nicholas Broad, Yanis Labrak, Shlok Deshmukh, Sid Kiblawi, Ayush Singh, Minh Chien Vu, Trishala Neeraj, Jonas Golde, Albert Villanova del Moral, Benjamin Beilharz
Datasets and Benchmarks Track
Branch & Learn for Recursively and Iteratively Solvable Problems in Predict+Optimize Xinyi Hu, Jasper Lee, Jimmy Lee, Allen Z. Zhong
Main Conference Track
Linear tree shap peng yu, Albert Bifet, Jesse Read, Chao Xu
Main Conference Track
Gradient Estimation with Discrete Stein Operators Jiaxin Shi, Yuhao Zhou, Jessica Hwang, Michalis K. Titsias, Lester W. Mackey
Main Conference Track
Rapidly Mixing Multiple-try Metropolis Algorithms for Model Selection Problems Hyunwoong Chang, Changwoo Lee, Zhao Tang Luo, Huiyan Sang, Quan Zhou
Main Conference Track
Distributionally Adaptive Meta Reinforcement Learning Anurag Ajay, Abhishek Gupta, Dibya Ghosh, Sergey Levine, Pulkit Agrawal
Main Conference Track
Toward Efficient Robust Training against Union of $\ell_p$ Threat Models Gaurang Sriramanan, Maharshi Gor, Soheil Feizi
Main Conference Track
Multi-view Subspace Clustering on Topological Manifold Shudong Huang, Hongjie Wu, Yazhou Ren, Ivor W. Tsang, Zenglin Xu, Wentao Feng, Jiancheng Lv
Main Conference Track
CLEAR: Generative Counterfactual Explanations on Graphs Jing Ma, Ruocheng Guo, Saumitra Mishra, Aidong Zhang, Jundong Li
Main Conference Track
Online Agnostic Multiclass Boosting Vinod Raman, Ambuj Tewari
Main Conference Track
A contrastive rule for meta-learning Nicolas Zucchet, Simon Schug, Johannes von Oswald, Dominic Zhao, João Sacramento
Main Conference Track
Distinguishing Learning Rules with Brain Machine Interfaces Jacob Portes, Christian Schmid, James M Murray
Main Conference Track
Efficient Training of Low-Curvature Neural Networks Suraj Srinivas, Kyle Matoba, Himabindu Lakkaraju, François Fleuret
Main Conference Track
Infinite-Fidelity Coregionalization for Physical Simulation Shibo Li, Zheng Wang, Robert Kirby, Shandian Zhe
Main Conference Track
Open High-Resolution Satellite Imagery: The WorldStrat Dataset – With Application to Super-Resolution Julien Cornebise, Ivan Oršolić, Freddie Kalaitzis
Datasets and Benchmarks Track
Evaluation beyond Task Performance: Analyzing Concepts in AlphaZero in Hex Charles Lovering, Jessica Forde, George Konidaris, Ellie Pavlick, Michael L. Littman
Main Conference Track
Semi-supervised Semantic Segmentation with Prototype-based Consistency Regularization Haiming Xu, Lingqiao Liu, Qiuchen Bian, Zhen Yang
Main Conference Track
Empirical Phase Diagram for Three-layer Neural Networks with Infinite Width Hanxu Zhou, Zhou Qixuan, Zhenyuan Jin, Tao Luo, Yaoyu Zhang, Zhi-Qin Xu
Main Conference Track
Benchmarking and Analyzing 3D Human Pose and Shape Estimation Beyond Algorithms Hui En Pang, Zhongang Cai, Lei Yang, Tianwei Zhang, Ziwei Liu
Datasets and Benchmarks Track
TTOpt: A Maximum Volume Quantized Tensor Train-based Optimization and its Application to Reinforcement Learning Konstantin Sozykin, Andrei Chertkov, Roman Schutski, Anh-Huy Phan, Andrzej S CICHOCKI, Ivan Oseledets
Main Conference Track
Diversified Recommendations for Agents with Adaptive Preferences William Brown, Arpit Agarwal
Main Conference Track
A Mixture Of Surprises for Unsupervised Reinforcement Learning Andrew Zhao, Matthieu Lin, Yangguang Li, Yong-jin Liu, Gao Huang
Main Conference Track
Deep Hierarchical Planning from Pixels Danijar Hafner, Kuang-Huei Lee, Ian Fischer, Pieter Abbeel
Main Conference Track
PeRFception: Perception using Radiance Fields Yoonwoo Jeong, Seungjoo Shin, Junha Lee, Chris Choy, Anima Anandkumar, Minsu Cho, Jaesik Park
Datasets and Benchmarks Track
Efficient Submodular Optimization under Noise: Local Search is Robust Lingxiao Huang, Yuyi Wang, Chunxue Yang, Huanjian Zhou
Main Conference Track
On the Generalization Power of the Overfitted Three-Layer Neural Tangent Kernel Model Peizhong Ju, Xiaojun Lin, Ness Shroff
Main Conference Track
Chromatic Correlation Clustering, Revisited Qing Xiu, Kai Han, Jing Tang, Shuang Cui, He Huang
Main Conference Track
Gradient-Free Methods for Deterministic and Stochastic Nonsmooth Nonconvex Optimization Tianyi Lin, Zeyu Zheng, Michael I. Jordan
Main Conference Track
Multilingual Abusive Comment Detection at Scale for Indic Languages Vikram Gupta, Sumegh Roychowdhury, Mithun Das, Somnath Banerjee, Punyajoy Saha, Binny Mathew, hastagiri prakash vanchinathan, Animesh Mukherjee
Datasets and Benchmarks Track
Generalized Delayed Feedback Model with Post-Click Information in Recommender Systems Jiaqi Yang, De-Chuan Zhan
Main Conference Track
A Communication-Efficient Distributed Gradient Clipping Algorithm for Training Deep Neural Networks Mingrui Liu, Zhenxun Zhuang, Yunwen Lei, Chunyang Liao
Main Conference Track
On Analyzing Generative and Denoising Capabilities of Diffusion-based Deep Generative Models Kamil Deja, Anna Kuzina, Tomasz Trzcinski, Jakub Tomczak
Main Conference Track
On the Tradeoff Between Robustness and Fairness Xinsong Ma, Zekai Wang, Weiwei Liu
Main Conference Track
Learning Expressive Meta-Representations with Mixture of Expert Neural Processes Qi Wang, Herke van Hoof
Main Conference Track
Learning Physical Dynamics with Subequivariant Graph Neural Networks Jiaqi Han, Wenbing Huang, Hengbo Ma, Jiachen Li, Josh Tenenbaum, Chuang Gan
Main Conference Track
DiSC: Differential Spectral Clustering of Features Ram Dyuthi Sristi, Gal Mishne, Ariel Jaffe
Main Conference Track
Learn what matters: cross-domain imitation learning with task-relevant embeddings Tim Franzmeyer, Philip Torr, João F. Henriques
Main Conference Track
UViM: A Unified Modeling Approach for Vision with Learned Guiding Codes Alexander Kolesnikov, André Susano Pinto, Lucas Beyer, Xiaohua Zhai, Jeremiah Harmsen, Neil Houlsby
Main Conference Track
Rotation-Equivariant Conditional Spherical Neural Fields for Learning a Natural Illumination Prior James Gardner, Bernhard Egger, William Smith
Main Conference Track
Proximal Learning With Opponent-Learning Awareness Stephen Zhao, Chris Lu, Roger B Grosse, Jakob Foerster
Main Conference Track
HyperTree Proof Search for Neural Theorem Proving Guillaume Lample, Timothee Lacroix, Marie-Anne Lachaux, Aurelien Rodriguez, Amaury Hayat, Thibaut Lavril, Gabriel Ebner, Xavier Martinet
Main Conference Track
The Policy-gradient Placement and Generative Routing Neural Networks for Chip Design Ruoyu Cheng, Xianglong Lyu, Yang Li, Junjie Ye, Jianye Hao, Junchi Yan
Main Conference Track
IMED-RL: Regret optimal learning of ergodic Markov decision processes Fabien Pesquerel, Odalric-Ambrym Maillard
Main Conference Track
Coresets for Wasserstein Distributionally Robust Optimization Problems Ruomin Huang, Jiawei Huang, Wenjie Liu, Hu Ding
Main Conference Track
SAMURAI: Shape And Material from Unconstrained Real-world Arbitrary Image collections Mark Boss, Andreas Engelhardt, Abhishek Kar, Yuanzhen Li, Deqing Sun, Jonathan Barron, Hendrik PA Lensch, Varun Jampani
Main Conference Track
Automatic differentiation of nonsmooth iterative algorithms Jerome Bolte, Edouard Pauwels, Samuel Vaiter
Main Conference Track
Wukong: A 100 Million Large-scale Chinese Cross-modal Pre-training Benchmark Jiaxi Gu, Xiaojun Meng, Guansong Lu, Lu Hou, Niu Minzhe, Xiaodan Liang, Lewei Yao, Runhui Huang, Wei Zhang, Xin Jiang, Chunjing XU, Hang Xu
Datasets and Benchmarks Track
Neural Abstractions Alessandro Abate, Alec Edwards, Mirco Giacobbe
Main Conference Track
Few-Shot Non-Parametric Learning with Deep Latent Variable Model Zhiying Jiang, Yiqin Dai, Ji Xin, Ming Li, Jimmy Lin
Main Conference Track
ST-Adapter: Parameter-Efficient Image-to-Video Transfer Learning Junting Pan, Ziyi Lin, Xiatian Zhu, Jing Shao, Hongsheng Li
Main Conference Track
Distilled Gradient Aggregation: Purify Features for Input Attribution in the Deep Neural Network Giyoung Jeon, Haedong Jeong, Jaesik Choi
Main Conference Track
Temporally Disentangled Representation Learning Weiran Yao, Guangyi Chen, Kun Zhang
Main Conference Track
Can Adversarial Training Be Manipulated By Non-Robust Features? Lue Tao, Lei Feng, Hongxin Wei, Jinfeng Yi, Sheng-Jun Huang, Songcan Chen
Main Conference Track
On the Effectiveness of Fine-tuning Versus Meta-reinforcement Learning Mandi Zhao, Pieter Abbeel, Stephen James
Main Conference Track
Generalizing Goal-Conditioned Reinforcement Learning with Variational Causal Reasoning Wenhao Ding, Haohong Lin, Bo Li, DING ZHAO
Main Conference Track
WinoGAViL: Gamified Association Benchmark to Challenge Vision-and-Language Models Yonatan Bitton, Nitzan Bitton Guetta, Ron Yosef, Yuval Elovici, Mohit Bansal, Gabriel Stanovsky, Roy Schwartz
Datasets and Benchmarks Track
Elucidating the Design Space of Diffusion-Based Generative Models Tero Karras, Miika Aittala, Timo Aila, Samuli Laine
Main Conference Track
TREC: Transient Redundancy Elimination-based Convolution Jiawei Guan, Feng Zhang, Jiesong Liu, Hsin-Hsuan Sung, Ruofan Wu, Xiaoyong Du, Xipeng Shen
Main Conference Track
Chaotic Regularization and Heavy-Tailed Limits for Deterministic Gradient Descent Soon Hoe Lim, Yijun Wan, Umut Simsekli
Main Conference Track
DARE: Disentanglement-Augmented Rationale Extraction Linan Yue, Qi Liu, Yichao Du, Yanqing An, Li Wang, Enhong Chen
Main Conference Track
The Gyro-Structure of Some Matrix Manifolds Xuan Son Nguyen
Main Conference Track
SMPL: Simulated Industrial Manufacturing and Process Control Learning Environments Mohan Zhang, Xiaozhou Wang, Benjamin Decardi-Nelson, Bo Song, An Zhang, Jinfeng Liu, Sile Tao, Jiayi Cheng, Xiaohong Liu, Dengdeng Yu, Matthew Poon, Animesh Garg
Datasets and Benchmarks Track
CoPur: Certifiably Robust Collaborative Inference via Feature Purification Jing Liu, Chulin Xie, Sanmi Koyejo, Bo Li
Main Conference Track
Toward Understanding Privileged Features Distillation in Learning-to-Rank Shuo Yang, Sujay Sanghavi, Holakou Rahmanian, Jan Bakus, Vishwanathan S. V. N.
Main Conference Track
Contrastive and Non-Contrastive Self-Supervised Learning Recover Global and Local Spectral Embedding Methods Randall Balestriero, Yann LeCun
Main Conference Track
Subgame Solving in Adversarial Team Games Brian Zhang, Luca Carminati, Federico Cacciamani, Gabriele Farina, Pierriccardo Olivieri, Nicola Gatti, Tuomas Sandholm
Main Conference Track
A framework for bilevel optimization that enables stochastic and global variance reduction algorithms Mathieu Dagréou, Pierre Ablin, Samuel Vaiter, Thomas Moreau
Main Conference Track
Predicting Cellular Responses to Novel Drug Perturbations at a Single-Cell Resolution Leon Hetzel, Simon Boehm, Niki Kilbertus, Stephan Günnemann, mohammad lotfollahi, Fabian J. Theis
Main Conference Track
Accelerated Projected Gradient Algorithms for Sparsity Constrained Optimization Problems Jan Harold Alcantara, Ching-pei Lee
Main Conference Track
The Stability-Efficiency Dilemma: Investigating Sequence Length Warmup for Training GPT Models Conglong Li, Minjia Zhang, Yuxiong He
Main Conference Track
Trading off Image Quality for Robustness is not Necessary with Regularized Deterministic Autoencoders Amrutha Saseendran, Kathrin Skubch, Stefan Falkner, Margret Keuper
Main Conference Track
Does Momentum Change the Implicit Regularization on Separable Data? Bohan Wang, Qi Meng, Huishuai Zhang, Ruoyu Sun, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu
Main Conference Track
Generalization Gap in Amortized Inference Mingtian Zhang, Peter Hayes, David Barber
Main Conference Track
Top Two Algorithms Revisited Marc Jourdan, Rémy Degenne, Dorian Baudry, Rianne de Heide, Emilie Kaufmann
Main Conference Track
Relation-Constrained Decoding for Text Generation Xiang Chen, Zhixian Yang, Xiaojun Wan
Main Conference Track
Learning General World Models in a Handful of Reward-Free Deployments Yingchen Xu, Jack Parker-Holder, Aldo Pacchiano, Philip Ball, Oleh Rybkin, S Roberts, Tim Rocktäschel, Edward Grefenstette
Main Conference Track
Bringing Image Scene Structure to Video via Frame-Clip Consistency of Object Tokens Elad Ben Avraham, Roei Herzig, Karttikeya Mangalam, Amir Bar, Anna Rohrbach, Leonid Karlinsky, Trevor Darrell, Amir Globerson
Main Conference Track
Probabilistic Transformer: Modelling Ambiguities and Distributions for RNA Folding and Molecule Design Jörg Franke, Frederic Runge, Frank Hutter
Main Conference Track
PulseImpute: A Novel Benchmark Task for Pulsative Physiological Signal Imputation Maxwell Xu, Alexander Moreno, Supriya Nagesh, Varol Aydemir, David Wetter, Santosh Kumar, James M. Rehg
Datasets and Benchmarks Track
Beyond Separability: Analyzing the Linear Transferability of Contrastive Representations to Related Subpopulations Jeff Z. HaoChen, Colin Wei, Ananya Kumar, Tengyu Ma
Main Conference Track
Precise Regret Bounds for Log-loss via a Truncated Bayesian Algorithm Changlong Wu, Mohsen Heidari, Ananth Grama, Wojciech Szpankowski
Main Conference Track
What are the best Systems? New Perspectives on NLP Benchmarking Pierre Colombo, Nathan Noiry, Ekhine Irurozki, Stephan Clémençon
Main Conference Track
Learning from Label Proportions by Learning with Label Noise Jianxin Zhang, Yutong Wang, Clay Scott
Main Conference Track
Dynamics of SGD with Stochastic Polyak Stepsizes: Truly Adaptive Variants and Convergence to Exact Solution Antonio Orvieto, Simon Lacoste-Julien, Nicolas Loizou
Main Conference Track
MORA: Improving Ensemble Robustness Evaluation with Model Reweighing Attack yunrui yu, Xitong Gao, Cheng-Zhong Xu
Main Conference Track
Faster and Scalable Algorithms for Densest Subgraph and Decomposition Elfarouk Harb, Kent Quanrud, Chandra Chekuri
Main Conference Track
Extrapolation and Spectral Bias of Neural Nets with Hadamard Product: a Polynomial Net Study Yongtao Wu, Zhenyu Zhu, Fanghui Liu, Grigorios Chrysos, Volkan Cevher
Main Conference Track
Cost-Sensitive Self-Training for Optimizing Non-Decomposable Metrics Harsh Rangwani, shrinivas ramasubramanian, Sho Takemori, Kato Takashi, Yuhei Umeda, Venkatesh Babu R
Main Conference Track
Tensor Wheel Decomposition and Its Tensor Completion Application Zhong-Cheng Wu, Ting-Zhu Huang, Liang-Jian Deng, Hong-Xia Dou, Deyu Meng
Main Conference Track
BOND: Benchmarking Unsupervised Outlier Node Detection on Static Attributed Graphs Kay Liu, Yingtong Dou, Yue Zhao, Xueying Ding, Xiyang Hu, Ruitong Zhang, Kaize Ding, Canyu Chen, Hao Peng, Kai Shu, Lichao Sun, Jundong Li, George H Chen, Zhihao Jia, Philip S Yu
Datasets and Benchmarks Track
Movement Penalized Bayesian Optimization with Application to Wind Energy Systems Shyam Sundhar Ramesh, Pier Giuseppe Sessa, Andreas Krause, Ilija Bogunovic
Main Conference Track
Associating Objects and Their Effects in Video through Coordination Games Erika Lu, Forrester Cole, Weidi Xie, Tali Dekel, Bill Freeman, Andrew Zisserman, Michael Rubinstein
Main Conference Track
Point-M2AE: Multi-scale Masked Autoencoders for Hierarchical Point Cloud Pre-training Renrui Zhang, Ziyu Guo, Peng Gao, Rongyao Fang, Bin Zhao, Dong Wang, Yu Qiao, Hongsheng Li
Main Conference Track
Exploring Example Influence in Continual Learning Qing Sun, Fan Lyu, Fanhua Shang, Wei Feng, Liang Wan
Main Conference Track
Subspace clustering in high-dimensions: Phase transitions & Statistical-to-Computational gap Luca Pesce, Bruno Loureiro, Florent Krzakala, Lenka Zdeborová
Main Conference Track
Self-Supervised Fair Representation Learning without Demographics Junyi Chai, Xiaoqian Wang
Main Conference Track
CEDe: A collection of expert-curated datasets with atom-level entity annotations for Optical Chemical Structure Recognition Rodrigo Hormazabal, Changyoung Park, Soonyoung Lee, Sehui Han, Yeonsik Jo, Jaewan Lee, Ahra Jo, Seung Hwan Kim, Jaegul Choo, Moontae Lee, Honglak Lee
Datasets and Benchmarks Track
How Mask Matters: Towards Theoretical Understandings of Masked Autoencoders Qi Zhang, Yifei Wang, Yisen Wang
Main Conference Track
Improving Out-of-Distribution Generalization by Adversarial Training with Structured Priors Qixun Wang, Yifei Wang, Hong Zhu, Yisen Wang
Main Conference Track
Graphein - a Python Library for Geometric Deep Learning and Network Analysis on Biomolecular Structures and Interaction Networks Arian Jamasb, Ramon Viñas Torné, Eric Ma, Yuanqi Du, Charles Harris, Kexin Huang, Dominic Hall, Pietro Lió, Tom Blundell
Main Conference Track
ZeroQuant: Efficient and Affordable Post-Training Quantization for Large-Scale Transformers Zhewei Yao, Reza Yazdani Aminabadi, Minjia Zhang, Xiaoxia Wu, Conglong Li, Yuxiong He
Main Conference Track
Simplified Graph Convolution with Heterophily Sudhanshu Chanpuriya, Cameron Musco
Main Conference Track
Signal Propagation in Transformers: Theoretical Perspectives and the Role of Rank Collapse Lorenzo Noci, Sotiris Anagnostidis, Luca Biggio, Antonio Orvieto, Sidak Pal Singh, Aurelien Lucchi
Main Conference Track
Maximum a posteriori natural scene reconstruction from retinal ganglion cells with deep denoiser priors Eric Wu, Nora Brackbill, Alexander Sher, Alan Litke, Eero P. Simoncelli, E. J. Chichilnisky
Main Conference Track
Imbalance Trouble: Revisiting Neural-Collapse Geometry Christos Thrampoulidis, Ganesh Ramachandra Kini, Vala Vakilian, Tina Behnia
Main Conference Track
ProtoX: Explaining a Reinforcement Learning Agent via Prototyping Ronilo Ragodos, Tong Wang, Qihang Lin, Xun Zhou
Main Conference Track
NOTE: Robust Continual Test-time Adaptation Against Temporal Correlation Taesik Gong, Jongheon Jeong, Taewon Kim, Yewon Kim, Jinwoo Shin, Sung-Ju Lee
Main Conference Track
Margin-Based Few-Shot Class-Incremental Learning with Class-Level Overfitting Mitigation Yixiong Zou, Shanghang Zhang, Yuhua Li, Ruixuan Li
Main Conference Track
First Hitting Diffusion Models for Generating Manifold, Graph and Categorical Data Mao Ye, Lemeng Wu, Qiang Liu
Main Conference Track
Forecasting Future World Events With Neural Networks Andy Zou, Tristan Xiao, Ryan Jia, Joe Kwon, Mantas Mazeika, Richard Li, Dawn Song, Jacob Steinhardt, Owain Evans, Dan Hendrycks
Datasets and Benchmarks Track
Human-Robotic Prosthesis as Collaborating Agents for Symmetrical Walking Ruofan Wu, Junmin Zhong, Brent Wallace, Xiang Gao, He Huang, Jennie Si
Main Conference Track
Support Recovery in Sparse PCA with Incomplete Data Hanbyul Lee, Qifan Song, Jean Honorio
Main Conference Track
Exponentially Improving the Complexity of Simulating the Weisfeiler-Lehman Test with Graph Neural Networks Anders Aamand, Justin Chen, Piotr Indyk, Shyam Narayanan, Ronitt Rubinfeld, Nicholas Schiefer, Sandeep Silwal, Tal Wagner
Main Conference Track
Zero-shot Transfer Learning within a Heterogeneous Graph via Knowledge Transfer Networks Minji Yoon, John Palowitch, Dustin Zelle, Ziniu Hu, Ruslan Salakhutdinov, Bryan Perozzi
Main Conference Track
Nonlinear Sufficient Dimension Reduction with a Stochastic Neural Network SIQI LIANG, Yan Sun, Faming Liang
Main Conference Track
Autoregressive Perturbations for Data Poisoning Pedro Sandoval-Segura, Vasu Singla, Jonas Geiping, Micah Goldblum, Tom Goldstein, David Jacobs
Main Conference Track
NodeFormer: A Scalable Graph Structure Learning Transformer for Node Classification Qitian Wu, Wentao Zhao, Zenan Li, David P Wipf, Junchi Yan
Main Conference Track
Is Integer Arithmetic Enough for Deep Learning Training? Alireza Ghaffari, Marzieh S. Tahaei, Mohammadreza Tayaranian, Masoud Asgharian, Vahid Partovi Nia
Main Conference Track
mRI: Multi-modal 3D Human Pose Estimation Dataset using mmWave, RGB-D, and Inertial Sensors Sizhe An, Yin Li, Umit Ogras
Datasets and Benchmarks Track
Effectiveness of Vision Transformer for Fast and Accurate Single-Stage Pedestrian Detection Jing Yuan, Panagiotis Barmpoutis, Tania Stathaki
Main Conference Track
ESCADA: Efficient Safety and Context Aware Dose Allocation for Precision Medicine Ilker Demirel, Ahmet Alparslan Celik, Cem Tekin
Main Conference Track
Grow and Merge: A Unified Framework for Continuous Categories Discovery Xinwei Zhang, Jianwen Jiang, Yutong Feng, Zhi-Fan Wu, Xibin Zhao, Hai Wan, Mingqian Tang, Rong Jin, Yue Gao
Main Conference Track
Category-Level 6D Object Pose Estimation in the Wild: A Semi-Supervised Learning Approach and A New Dataset Yang Fu, Xiaolong Wang
Main Conference Track
Change Event Dataset for Discovery from Spatio-temporal Remote Sensing Imagery Utkarsh Mall, Bharath Hariharan, Kavita Bala
Datasets and Benchmarks Track
Improved Algorithms for Neural Active Learning Yikun Ban, Yuheng Zhang, Hanghang Tong, Arindam Banerjee, Jingrui He
Main Conference Track
Robust Calibration with Multi-domain Temperature Scaling Yaodong Yu, Stephen Bates, Yi Ma, Michael I. Jordan
Main Conference Track
Independence Testing-Based Approach to Causal Discovery under Measurement Error and Linear Non-Gaussian Models Haoyue Dai, Peter Spirtes, Kun Zhang
Main Conference Track
CUP: Critic-Guided Policy Reuse Jin Zhang, Siyuan Li, Chongjie Zhang
Main Conference Track
Local Identifiability of Deep ReLU Neural Networks: the Theory Joachim Bona-Pellissier, François Malgouyres, Francois Bachoc
Main Conference Track
DOMINO: Decomposed Mutual Information Optimization for Generalized Context in Meta-Reinforcement Learning Yao Mu, Yuzheng Zhuang, Fei Ni, Bin Wang, Jianyu Chen, Jianye Hao, Ping Luo
Main Conference Track
Generalization Bounds with Minimal Dependency on Hypothesis Class via Distributionally Robust Optimization Yibo Zeng, Henry Lam
Main Conference Track
QUARK: Controllable Text Generation with Reinforced Unlearning Ximing Lu, Sean Welleck, Jack Hessel, Liwei Jiang, Lianhui Qin, Peter West, Prithviraj Ammanabrolu, Yejin Choi
Main Conference Track
Safe Opponent-Exploitation Subgame Refinement Mingyang Liu, Chengjie Wu, Qihan Liu, Yansen Jing, Jun Yang, Pingzhong Tang, Chongjie Zhang
Main Conference Track
Parameter-free Dynamic Graph Embedding for Link Prediction Jiahao Liu, Dongsheng Li, Hansu Gu, Tun Lu, Peng Zhang, Ning Gu
Main Conference Track
Towards a Unified Framework for Uncertainty-aware Nonlinear Variable Selection with Theoretical Guarantees Wenying Deng, Beau Coker, Rajarshi Mukherjee, Jeremiah Liu, Brent Coull
Main Conference Track
Non-Markovian Reward Modelling from Trajectory Labels via Interpretable Multiple Instance Learning Joseph Early, Tom Bewley, Christine Evers, Sarvapali Ramchurn
Main Conference Track
Explaining Preferences with Shapley Values Robert Hu, Siu Lun Chau, Jaime Ferrando Huertas, Dino Sejdinovic
Main Conference Track
Structuring Uncertainty for Fine-Grained Sampling in Stochastic Segmentation Networks Frank Nussbaum, Jakob Gawlikowski, Julia Niebling
Main Conference Track
Fair Bayes-Optimal Classifiers Under Predictive Parity Xianli Zeng, Edgar Dobriban, Guang Cheng
Main Conference Track
Pre-Train Your Loss: Easy Bayesian Transfer Learning with Informative Priors Ravid Shwartz-Ziv, Micah Goldblum, Hossein Souri, Sanyam Kapoor, Chen Zhu, Yann LeCun, Andrew G Wilson
Main Conference Track
Unsupervised Adaptation from Repeated Traversals for Autonomous Driving Yurong You, Cheng Perng Phoo, Katie Luo, Travis Zhang, Wei-Lun Chao, Bharath Hariharan, Mark Campbell, Kilian Q. Weinberger
Main Conference Track
Training language models to follow instructions with human feedback Long Ouyang, Jeffrey Wu, Xu Jiang, Diogo Almeida, Carroll Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, John Schulman, Jacob Hilton, Fraser Kelton, Luke Miller, Maddie Simens, Amanda Askell, Peter Welinder, Paul F Christiano, Jan Leike, Ryan Lowe
Main Conference Track
Byzantine Spectral Ranking Arnhav Datar, Arun Rajkumar, John Augustine
Main Conference Track
Non-rigid Point Cloud Registration with Neural Deformation Pyramid YANG LI, Tatsuya Harada
Main Conference Track
Provably tuning the ElasticNet across instances Maria-Florina F Balcan, Misha Khodak, Dravyansh Sharma, Ameet Talwalkar
Main Conference Track
PlasticityNet: Learning to Simulate Metal, Sand, and Snow for Optimization Time Integration Xuan Li, Yadi Cao, Minchen Li, Yin Yang, Craig Schroeder, Chenfanfu Jiang
Main Conference Track
Synthetic Model Combination: An Instance-wise Approach to Unsupervised Ensemble Learning Alex Chan, Mihaela van der Schaar
Main Conference Track
Power and limitations of single-qubit native quantum neural networks Zhan Yu, Hongshun Yao, Mujin Li, Xin Wang
Main Conference Track
Hedging as Reward Augmentation in Probabilistic Graphical Models Debarun Bhattacharjya, Radu Marinescu
Main Conference Track
Debiased, Longitudinal and Coordinated Drug Recommendation through Multi-Visit Clinic Records Hongda Sun, Shufang Xie, Shuqi Li, Yuhan Chen, Ji-Rong Wen, Rui Yan
Main Conference Track
Disentangling Causal Effects from Sets of Interventions in the Presence of Unobserved Confounders Olivier Jeunen, Ciarán Gilligan-Lee, Rishabh Mehrotra, Mounia Lalmas
Main Conference Track
MATE: Benchmarking Multi-Agent Reinforcement Learning in Distributed Target Coverage Control Xuehai Pan, Mickel Liu, Fangwei Zhong, Yaodong Yang, Song-Chun Zhu, Yizhou Wang
Datasets and Benchmarks Track
Receding Horizon Inverse Reinforcement Learning Yiqing Xu, Wei Gao, David Hsu
Main Conference Track
A Reparametrization-Invariant Sharpness Measure Based on Information Geometry Cheongjae Jang, Sungyoon Lee, Frank Park, Yung-Kyun Noh
Main Conference Track
Hyper-Representations as Generative Models: Sampling Unseen Neural Network Weights Konstantin Schürholt, Boris Knyazev, Xavier Giró-i-Nieto, Damian Borth
Main Conference Track
Multi-Game Decision Transformers Kuang-Huei Lee, Ofir Nachum, Mengjiao (Sherry) Yang, Lisa Lee, Daniel Freeman, Sergio Guadarrama, Ian Fischer, Winnie Xu, Eric Jang, Henryk Michalewski, Igor Mordatch
Main Conference Track
Improving Transformer with an Admixture of Attention Heads Tan Nguyen, Tam Nguyen, Hai Do, Khai Nguyen, Vishwanath Saragadam, Minh Pham, Khuong Duy Nguyen, Nhat Ho, Stanley Osher
Main Conference Track
Flexible Diffusion Modeling of Long Videos William Harvey, Saeid Naderiparizi, Vaden Masrani, Christian Weilbach, Frank Wood
Main Conference Track
Towards Reasonable Budget Allocation in Untargeted Graph Structure Attacks via Gradient Debias Zihan Liu, Yun Luo, Lirong Wu, Zicheng Liu, Stan Z. Li
Main Conference Track
ToDD: Topological Compound Fingerprinting in Computer-Aided Drug Discovery Andaç Demir, Baris Coskunuzer, Yulia Gel, Ignacio Segovia-Dominguez, Yuzhou Chen, Bulent Kiziltan
Main Conference Track
Geo-SIC: Learning Deformable Geometric Shapes in Deep Image Classifiers Jian Wang, Miaomiao Zhang
Main Conference Track
A Survey and Datasheet Repository of Publicly Available US Criminal Justice Datasets Miri Zilka, Bradley Butcher, Adrian Weller
Datasets and Benchmarks Track
Segmenting Moving Objects via an Object-Centric Layered Representation Junyu Xie, Weidi Xie, Andrew Zisserman
Main Conference Track
NAS-Bench-Suite-Zero: Accelerating Research on Zero Cost Proxies Arjun Krishnakumar, Colin White, Arber Zela, Renbo Tu, Mahmoud Safari, Frank Hutter
Datasets and Benchmarks Track
On the Strong Correlation Between Model Invariance and Generalization Weijian Deng, Stephen Gould, Liang Zheng
Main Conference Track
On Scalable Testing of Samplers Yash Pote, Kuldeep S Meel
Main Conference Track
How and Why to Manipulate Your Own Agent: On the Incentives of Users of Learning Agents Yoav Kolumbus, Noam Nisan
Main Conference Track
LIPS - Learning Industrial Physical Simulation benchmark suite Milad LEYLI ABADI, Antoine Marot, Jérôme Picault, David Danan, Mouadh Yagoubi, Benjamin Donnot, Seif Attoui, Pavel Dimitrov, Asma Farjallah, Clement Etienam
Datasets and Benchmarks Track
FlyView: a bio-informed optical flow truth dataset for visual navigation using panoramic stereo vision Alix Leroy, Graham W. Taylor
Datasets and Benchmarks Track
Controllable Text Generation with Neurally-Decomposed Oracle Tao Meng, Sidi Lu, Nanyun Peng, Kai-Wei Chang
Main Conference Track
Active Learning Helps Pretrained Models Learn the Intended Task Alex Tamkin, Dat Nguyen, Salil Deshpande, Jesse Mu, Noah Goodman
Main Conference Track
Pragmatically Learning from Pedagogical Demonstrations in Multi-Goal Environments Hugo Caselles-Dupré, Olivier Sigaud, Mohamed CHETOUANI
Main Conference Track
Beyond black box densities: Parameter learning for the deviated components Dat Do, Nhat Ho, Xuanlong Nguyen
Main Conference Track
Statistical, Robustness, and Computational Guarantees for Sliced Wasserstein Distances Sloan Nietert, Ziv Goldfeld, Ritwik Sadhu, Kengo Kato
Main Conference Track
Oracle Inequalities for Model Selection in Offline Reinforcement Learning Jonathan N Lee, George Tucker, Ofir Nachum, Bo Dai, Emma Brunskill
Main Conference Track
Model-Based Opponent Modeling XiaoPeng Yu, Jiechuan Jiang, Wanpeng Zhang, Haobin Jiang, Zongqing Lu
Main Conference Track
What is Where by Looking: Weakly-Supervised Open-World Phrase-Grounding without Text Inputs Tal Shaharabany, Yoad Tewel, Lior Wolf
Main Conference Track
DeepMed: Semiparametric Causal Mediation Analysis with Debiased Deep Learning Siqi Xu, Lin Liu, Zhonghua Liu
Main Conference Track
On the Learning Mechanisms in Physical Reasoning Shiqian Li, Kewen Wu, Chi Zhang, Yixin Zhu
Main Conference Track
A Continuous Time Framework for Discrete Denoising Models Andrew Campbell, Joe Benton, Valentin De Bortoli, Thomas Rainforth, George Deligiannidis, Arnaud Doucet
Main Conference Track
Simple Mechanisms for Welfare Maximization in Rich Advertising Auctions Gagan Aggarwal, Kshipra Bhawalkar, Aranyak Mehta, Divyarthi Mohan, Alexandros Psomas
Main Conference Track
Continuously Tempered PDMP samplers Matthew Sutton, Robert Salomone, Augustin Chevallier, Paul Fearnhead
Main Conference Track
Distributed Influence-Augmented Local Simulators for Parallel MARL in Large Networked Systems Miguel Suau, Jinke He, Mustafa Mert Çelikok, Matthijs Spaan, Frans Oliehoek
Main Conference Track
Tight Mutual Information Estimation With Contrastive Fenchel-Legendre Optimization Qing Guo, Junya Chen, Dong Wang, Yuewei Yang, Xinwei Deng, Jing Huang, Larry Carin, Fan Li, Chenyang Tao
Main Conference Track
Exploring the Algorithm-Dependent Generalization of AUPRC Optimization with List Stability Peisong Wen, Qianqian Xu, Zhiyong Yang, Yuan He, Qingming Huang
Main Conference Track
LTMD: Learning Improvement of Spiking Neural Networks with Learnable Thresholding Neurons and Moderate Dropout SIQI WANG, Tee Hiang Cheng, Meng-Hiot Lim
Main Conference Track
TransBoost: Improving the Best ImageNet Performance using Deep Transduction Omer Belhasin, Guy Bar-Shalom, Ran El-Yaniv
Main Conference Track
Sparse Probabilistic Circuits via Pruning and Growing Meihua Dang, Anji Liu, Guy Van den Broeck
Main Conference Track
Adam Can Converge Without Any Modification On Update Rules Yushun Zhang, Congliang Chen, Naichen Shi, Ruoyu Sun, Zhi-Quan Luo
Main Conference Track
Nonlinear MCMC for Bayesian Machine Learning James Vuckovic
Main Conference Track
Continual learning: a feature extraction formalization, an efficient algorithm, and fundamental obstructions Binghui Peng, Andrej Risteski
Main Conference Track
IKEA-Manual: Seeing Shape Assembly Step by Step Ruocheng Wang, Yunzhi Zhang, Jiayuan Mao, Ran Zhang, Chin-Yi Cheng, Jiajun Wu
Datasets and Benchmarks Track
M³ViT: Mixture-of-Experts Vision Transformer for Efficient Multi-task Learning with Model-Accelerator Co-design hanxue liang, Zhiwen Fan, Rishov Sarkar, Ziyu Jiang, Tianlong Chen, Kai Zou, Yu Cheng, Cong Hao, Zhangyang Wang
Main Conference Track
When to Make Exceptions: Exploring Language Models as Accounts of Human Moral Judgment Zhijing Jin, Sydney Levine, Fernando Gonzalez Adauto, Ojasv Kamal, Maarten Sap, Mrinmaya Sachan, Rada Mihalcea, Josh Tenenbaum, Bernhard Schölkopf
Main Conference Track
Exponential Family Model-Based Reinforcement Learning via Score Matching Gene Li, Junbo Li, Anmol Kabra, Nati Srebro, Zhaoran Wang, Zhuoran Yang
Main Conference Track
Monte Carlo Tree Search based Variable Selection for High Dimensional Bayesian Optimization Lei Song, Ke Xue, Xiaobin Huang, Chao Qian
Main Conference Track
OpenSRH: optimizing brain tumor surgery using intraoperative stimulated Raman histology Cheng Jiang, Asadur Chowdury, Xinhai Hou, Akhil Kondepudi, Christian Freudiger, Kyle Conway, Sandra Camelo-Piragua, Daniel Orringer, Honglak Lee, Todd Hollon
Datasets and Benchmarks Track
Assistive Teaching of Motor Control Tasks to Humans Megha Srivastava, Erdem Biyik, Suvir Mirchandani, Noah Goodman, Dorsa Sadigh
Main Conference Track
Retrospective Adversarial Replay for Continual Learning Lilly Kumari, Shengjie Wang, Tianyi Zhou, Jeff A Bilmes
Main Conference Track
Unsupervised Image-to-Image Translation with Density Changing Regularization Shaoan Xie, Qirong Ho, Kun Zhang
Main Conference Track
CASA: Category-agnostic Skeletal Animal Reconstruction Yuefan Wu, Zeyuan Chen, Shaowei Liu, Zhongzheng Ren, Shenlong Wang
Main Conference Track
Regret Bounds for Information-Directed Reinforcement Learning Botao Hao, Tor Lattimore
Main Conference Track
Adversarial Reprogramming Revisited Matthias Englert, Ranko Lazic
Main Conference Track
Coded Residual Transform for Generalizable Deep Metric Learning Shichao Kan, Yixiong Liang, Min Li, Yigang Cen, Jianxin Wang, Zhihai He
Main Conference Track
When Does Differentially Private Learning Not Suffer in High Dimensions? Xuechen Li, Daogao Liu, Tatsunori B Hashimoto, Huseyin A. Inan, Janardhan Kulkarni, Yin-Tat Lee, Abhradeep Guha Thakurta
Main Conference Track
Nearly Optimal Best-of-Both-Worlds Algorithms for Online Learning with Feedback Graphs Shinji Ito, Taira Tsuchiya, Junya Honda
Main Conference Track
Few-shot Task-agnostic Neural Architecture Search for Distilling Large Language Models Dongkuan (DK) Xu, Subhabrata Mukherjee, Xiaodong Liu, Debadeepta Dey, Wenhui Wang, Xiang Zhang, Ahmed Awadallah, Jianfeng Gao
Main Conference Track
Universal Rates for Interactive Learning Steve Hanneke, Amin Karbasi, Shay Moran, Grigoris Velegkas
Main Conference Track
Learning Active Camera for Multi-Object Navigation Peihao Chen, Dongyu Ji, Kunyang Lin, Weiwen Hu, Wenbing Huang, Thomas Li, Mingkui Tan, Chuang Gan
Main Conference Track
Knowledge Distillation: Bad Models Can Be Good Role Models Gal Kaplun, Eran Malach, Preetum Nakkiran, Shai Shalev-Shwartz
Main Conference Track
On Computing Probabilistic Explanations for Decision Trees Marcelo Arenas, Pablo Barceló, Miguel Romero Orth, Bernardo Subercaseaux
Main Conference Track
Masked Autoencoders that Listen Po-Yao Huang, Hu Xu, Juncheng Li, Alexei Baevski, Michael Auli, Wojciech Galuba, Florian Metze, Christoph Feichtenhofer
Main Conference Track
AUTOMATA: Gradient Based Data Subset Selection for Compute-Efficient Hyper-parameter Tuning Krishnateja Killamsetty, Guttu Sai Abhishek, Aakriti Lnu, Ganesh Ramakrishnan, Alexandre Evfimievski, Lucian Popa, Rishabh Iyer
Main Conference Track
DeepTOP: Deep Threshold-Optimal Policy for MDPs and RMABs Khaled Nakhleh, I-Hong Hou
Main Conference Track
Is a Modular Architecture Enough? Sarthak Mittal, Yoshua Bengio, Guillaume Lajoie
Main Conference Track
Exploration via Planning for Information about the Optimal Trajectory Viraj Mehta, Ian Char, Joseph Abbate, Rory Conlin, Mark Boyer, Stefano Ermon, Jeff G. Schneider, Willie Neiswanger
Main Conference Track
Subquadratic Kronecker Regression with Applications to Tensor Decomposition Matthew Fahrbach, Gang Fu, Mehrdad Ghadiri
Main Conference Track
Robust Anytime Learning of Markov Decision Processes Marnix Suilen, Thiago D. Simão, David B. Parker, Nils Jansen
Main Conference Track
Discovering Design Concepts for CAD Sketches Yuezhi Yang, Hao Pan
Main Conference Track
Learning Distributed and Fair Policies for Network Load Balancing as Markov Potential Game Zhiyuan Yao, Zihan Ding
Main Conference Track
Para-CFlows: $C^k$-universal diffeomorphism approximators as superior neural surrogates Junlong Lyu, Zhitang Chen, Chang Feng, Wenjing Cun, Shengyu Zhu, Yanhui Geng, ZHIJIE XU, Chen Yongwei
Main Conference Track
NCP: Neural Correspondence Prior for Effective Unsupervised Shape Matching Souhaib Attaiki, Maks Ovsjanikov
Main Conference Track
Efficient Spatially Sparse Inference for Conditional GANs and Diffusion Models Muyang Li, Ji Lin, Chenlin Meng, Stefano Ermon, Song Han, Jun-Yan Zhu
Main Conference Track
A Greek Parliament Proceedings Dataset for Computational Linguistics and Political Analysis Konstantina Dritsa, Aikaterini Thoma, Ioannis Pavlopoulos, Panos Louridas
Datasets and Benchmarks Track
Multi-objective Deep Data Generation with Correlated Property Control Shiyu Wang, Xiaojie Guo, Xuanyang Lin, Bo Pan, Yuanqi Du, Yinkai Wang, Yanfang Ye, Ashley Petersen, Austin Leitgeb, Saleh Alkhalifa, Kevin Minbiole, William M. Wuest, Amarda Shehu, Liang Zhao
Main Conference Track
Domain Adaptation meets Individual Fairness. And they get along. Debarghya Mukherjee, Felix Petersen, Mikhail Yurochkin, Yuekai Sun
Main Conference Track
An Asymptotically Optimal Batched Algorithm for the Dueling Bandit Problem Arpit Agarwal, Rohan Ghuge, viswanath nagarajan
Main Conference Track
Enhanced Bilevel Optimization via Bregman Distance Feihu Huang, Junyi Li, Shangqian Gao, Heng Huang
Main Conference Track
SAVi++: Towards End-to-End Object-Centric Learning from Real-World Videos Gamaleldin Elsayed, Aravindh Mahendran, Sjoerd van Steenkiste, Klaus Greff, Michael Mozer, Thomas Kipf
Main Conference Track
Reincarnating Reinforcement Learning: Reusing Prior Computation to Accelerate Progress Rishabh Agarwal, Max Schwarzer, Pablo Samuel Castro, Aaron C. Courville, Marc Bellemare
Main Conference Track
Global Linear and Local Superlinear Convergence of IRLS for Non-Smooth Robust Regression Liangzu Peng, Christian Kümmerle, Rene Vidal
Main Conference Track
Rashomon Capacity: A Metric for Predictive Multiplicity in Classification Hsiang Hsu, Flavio Calmon
Main Conference Track
Inducing Equilibria via Incentives: Simultaneous Design-and-Play Ensures Global Convergence Boyi Liu, Jiayang Li, Zhuoran Yang, Hoi-To Wai, Mingyi Hong, Yu Nie, Zhaoran Wang
Main Conference Track
Learning with convolution and pooling operations in kernel methods Theodor Misiakiewicz, Song Mei
Main Conference Track
In Differential Privacy, There is Truth: on Vote-Histogram Leakage in Ensemble Private Learning JIAQI WANG, Roei Schuster, I Shumailov, David Lie, Nicolas Papernot
Main Conference Track
Estimating graphical models for count data with applications to single-cell gene network Feiyi Xiao, Junjie Tang, Huaying Fang, Ruibin Xi
Main Conference Track
Online Minimax Multiobjective Optimization: Multicalibeating and Other Applications Daniel D. Lee, Georgy Noarov, Mallesh Pai, Aaron Roth
Main Conference Track
Roadblocks for Temporarily Disabling Shortcuts and Learning New Knowledge Hongjing Niu, Hanting Li, Feng Zhao, Bin Li
Main Conference Track
Random Rank: The One and Only Strategyproof and Proportionally Fair Randomized Facility Location Mechanism Haris Aziz, Alexander Lam, Mashbat Suzuki, Toby Walsh
Main Conference Track
Distributionally robust weighted k-nearest neighbors Shixiang Zhu, Liyan Xie, Minghe Zhang, Rui Gao, Yao Xie
Main Conference Track
A Character-Level Length-Control Algorithm for Non-Autoregressive Sentence Summarization Puyuan Liu, Xiang Zhang, Lili Mou
Main Conference Track
Neural Lyapunov Control of Unknown Nonlinear Systems with Stability Guarantees Ruikun Zhou, Thanin Quartz, Hans De Sterck, Jun Liu
Main Conference Track
Minimax Regret for Cascading Bandits Daniel Vial, Sujay Sanghavi, Sanjay Shakkottai, R. Srikant
Main Conference Track
Mean Estimation with User-level Privacy under Data Heterogeneity Rachel Cummings, Vitaly Feldman, Audra McMillan, Kunal Talwar
Main Conference Track
Proppo: a Message Passing Framework for Customizable and Composable Learning Algorithms Paavo Parmas, Takuma Seno
Main Conference Track
A Lower Bound of Hash Codes' Performance Xiaosu Zhu, Jingkuan Song, Yu Lei, Lianli Gao, Hengtao Shen
Main Conference Track
Self-Supervised Image Restoration with Blurry and Noisy Pairs Zhilu Zhang, RongJian Xu, Ming Liu, Zifei Yan, Wangmeng Zuo
Main Conference Track
Embracing Consistency: A One-Stage Approach for Spatio-Temporal Video Grounding Yang Jin, yongzhi li, Zehuan Yuan, Yadong Mu
Main Conference Track
Pitfalls of Epistemic Uncertainty Quantification through Loss Minimisation Viktor Bengs, Eyke Hüllermeier, Willem Waegeman
Main Conference Track
Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset Peter Henderson, Mark Krass, Lucia Zheng, Neel Guha, Christopher D Manning, Dan Jurafsky, Daniel Ho
Datasets and Benchmarks Track
Active-Passive SimStereo - Benchmarking the Cross-Generalization Capabilities of Deep Learning-based Stereo Methods Laurent Jospin, Allen Antony, Lian Xu, Hamid Laga, Farid Boussaid, Mohammed Bennamoun
Datasets and Benchmarks Track
Back Razor: Memory-Efficient Transfer Learning by Self-Sparsified Backpropagation Ziyu Jiang, Xuxi Chen, Xueqin Huang, Xianzhi Du, Denny Zhou, Zhangyang Wang
Main Conference Track
Patching open-vocabulary models by interpolating weights Gabriel Ilharco, Mitchell Wortsman, Samir Yitzhak Gadre, Shuran Song, Hannaneh Hajishirzi, Simon Kornblith, Ali Farhadi, Ludwig Schmidt
Main Conference Track
Training stochastic stabilized supralinear networks by dynamics-neutral growth Wayne Soo, Mate Lengyel
Main Conference Track
Post-hoc estimators for learning to defer to an expert Harikrishna Narasimhan, Wittawat Jitkrittum, Aditya K Menon, Ankit Rawat, Sanjiv Kumar
Main Conference Track
Learning Generalizable Part-based Feature Representation for 3D Point Clouds Xin Wei, Xiang Gu, Jian Sun
Main Conference Track
FourierFormer: Transformer Meets Generalized Fourier Integral Theorem Tan Nguyen, Minh Pham, Tam Nguyen, Khai Nguyen, Stanley Osher, Nhat Ho
Main Conference Track
Learning Multi-resolution Functional Maps with Spectral Attention for Robust Shape Matching Lei Li, Nicolas Donati, Maks Ovsjanikov
Main Conference Track
Label-invariant Augmentation for Semi-Supervised Graph Classification Han Yue, Chunhui Zhang, Chuxu Zhang, Hongfu Liu
Main Conference Track
Practical Adversarial Multivalid Conformal Prediction Osbert Bastani, Varun Gupta, Christopher Jung, Georgy Noarov, Ramya Ramalingam, Aaron Roth
Main Conference Track
Test-Time Training with Masked Autoencoders Yossi Gandelsman, Yu Sun, Xinlei Chen, Alexei Efros
Main Conference Track
Constraining Gaussian Processes to Systems of Linear Ordinary Differential Equations Andreas Besginow, Markus Lange-Hegermann
Main Conference Track
So3krates: Equivariant attention for interactions on arbitrary length-scales in molecular systems Thorben Frank, Oliver Unke, Klaus-Robert Müller
Main Conference Track
HyperDomainNet: Universal Domain Adaptation for Generative Adversarial Networks Aibek Alanov, Vadim Titov, Dmitry P Vetrov
Main Conference Track
Multiagent Q-learning with Sub-Team Coordination Wenhan Huang, Kai Li, Kun Shao, Tianze Zhou, Matthew Taylor, Jun Luo, Dongge Wang, Hangyu Mao, Jianye Hao, Jun Wang, Xiaotie Deng
Main Conference Track
CLiMB: A Continual Learning Benchmark for Vision-and-Language Tasks Tejas Srinivasan, Ting-Yun Chang, Leticia Pinto Alva, Georgios Chochlakis, Mohammad Rostami, Jesse Thomason
Datasets and Benchmarks Track
Bidirectional Learning for Offline Infinite-width Model-based Optimization Can Chen, Yingxueff Zhang, Jie Fu, Xue (Steve) Liu, Mark Coates
Main Conference Track
Differentially Private Model Compression FatemehSadat Mireshghallah, Arturs Backurs, Huseyin A. Inan, Lukas Wutschitz, Janardhan Kulkarni
Main Conference Track
Dual-Curriculum Contrastive Multi-Instance Learning for Cancer Prognosis Analysis with Whole Slide Images CHAO TU, YU ZHANG, Zhenyuan Ning
Main Conference Track
Meta-Complementing the Semantics of Short Texts in Neural Topic Models Delvin Ce Zhang, Hady Lauw
Main Conference Track
Unified Optimal Transport Framework for Universal Domain Adaptation Wanxing Chang, Ye Shi, Hoang Tuan, Jingya Wang
Main Conference Track
GBA: A Tuning-free Approach to Switch between Synchronous and Asynchronous Training for Recommendation Models Wenbo Su, Yuanxing Zhang, Yufeng Cai, Kaixu Ren, Pengjie Wang, Huimin Yi, Yue Song, Jing Chen, Hongbo Deng, Jian Xu, Lin Qu, Bo Zheng
Main Conference Track
TUSK: Task-Agnostic Unsupervised Keypoints Yuhe Jin, Weiwei Sun, Jan Hosang, Eduard Trulls, Kwang Moo Yi
Main Conference Track
Multi-block Min-max Bilevel Optimization with Applications in Multi-task Deep AUC Maximization Quanqi Hu, YONGJIAN ZHONG, Tianbao Yang
Main Conference Track
Coresets for Vertical Federated Learning: Regularized Linear Regression and $K$-Means Clustering Lingxiao Huang, Zhize Li, Jialin Sun, Haoyu Zhao
Main Conference Track
Class-Aware Adversarial Transformers for Medical Image Segmentation Chenyu You, Ruihan Zhao, Fenglin Liu, Siyuan Dong, Sandeep Chinchali, Ufuk Topcu, Lawrence Staib, James Duncan
Main Conference Track
MCL-GAN: Generative Adversarial Networks with Multiple Specialized Discriminators Jinyoung Choi, Bohyung Han
Main Conference Track
Unsupervised Visual Representation Learning via Mutual Information Regularized Assignment Dong Hoon Lee, Sungik Choi, Hyunwoo J Kim, Sae-Young Chung
Main Conference Track
Mind Reader: Reconstructing complex images from brain activities Sikun Lin, Thomas Sprague, Ambuj K Singh
Main Conference Track
A Few Expert Queries Suffices for Sample-Efficient RL with Resets and Linear Value Approximation Philip Amortila, Nan Jiang, Dhruv Madeka, Dean P. Foster
Main Conference Track
Subsidiary Prototype Alignment for Universal Domain Adaptation Jogendra Nath Kundu, Suvaansh Bhambri, Akshay R Kulkarni, Hiran Sarkar, Varun Jampani, Venkatesh Babu R
Main Conference Track
Dynamic Inverse Reinforcement Learning for Characterizing Animal Behavior Zoe Ashwood, Aditi Jha, Jonathan W Pillow
Main Conference Track
FedRolex: Model-Heterogeneous Federated Learning with Rolling Sub-Model Extraction Samiul Alam, Luyang Liu, Ming Yan, Mi Zhang
Main Conference Track
Multi-Lingual Acquisition on Multimodal Pre-training for Cross-modal Retrieval Liang Zhang, Anwen Hu, Qin Jin
Main Conference Track
Manifold Interpolating Optimal-Transport Flows for Trajectory Inference Guillaume Huguet, Daniel Sumner Magruder, Alexander Tong, Oluwadamilola Fasina, Manik Kuchroo, Guy Wolf, Smita Krishnaswamy
Main Conference Track
Depth is More Powerful than Width with Prediction Concatenation in Deep Forest Shen-Huan Lyu, Yi-Xiao He, Zhi-Hua Zhou
Main Conference Track
Logical Activation Functions: Logit-space equivalents of Probabilistic Boolean Operators Scott Lowe, Robert Earle, Jason d'Eon, Thomas P. Trappenberg, Sageev Oore
Main Conference Track
An Investigation into Whitening Loss for Self-supervised Learning Xi Weng, Lei Huang, Lei Zhao, Rao Anwer, Salman H Khan, Fahad Shahbaz Khan
Main Conference Track
Geometric Knowledge Distillation: Topology Compression for Graph Neural Networks Chenxiao Yang, Qitian Wu, Junchi Yan
Main Conference Track
A Benchmark for Compositional Visual Reasoning Aimen Zerroug, Mohit Vaishnav, Julien Colin, Sebastian Musslick, Thomas Serre
Datasets and Benchmarks Track
Learning Articulated Rigid Body Dynamics with Lagrangian Graph Neural Network Ravinder Bhattoo, Sayan Ranu, N M Anoop Krishnan
Main Conference Track
Myriad: a real-world testbed to bridge trajectory optimization and deep learning Nikolaus Howe, Simon Dufort-Labbé, Nitarshan Rajkumar, Pierre-Luc Bacon
Datasets and Benchmarks Track
Batch Bayesian optimisation via density-ratio estimation with guarantees Rafael Oliveira, Louis Tiao, Fabio T Ramos
Main Conference Track
Amplifying Membership Exposure via Data Poisoning Yufei Chen, Chao Shen, Yun Shen, Cong Wang, Yang Zhang
Main Conference Track
Boosting the Transferability of Adversarial Attacks with Reverse Adversarial Perturbation Zeyu Qin, Yanbo Fan, Yi Liu, Li Shen, Yong Zhang, Jue Wang, Baoyuan Wu
Main Conference Track
Extra-Newton: A First Approach to Noise-Adaptive Accelerated Second-Order Methods Kimon Antonakopoulos, Ali Kavis, Volkan Cevher
Main Conference Track
FETA: Towards Specializing Foundational Models for Expert Task Applications Amit Alfassy, Assaf Arbelle, Oshri Halimi, Sivan Harary, Roei Herzig, Eli Schwartz, Rameswar Panda, Michele Dolfi, Christoph Auer, Peter Staar, Kate Saenko, Rogerio Feris, Leonid Karlinsky
Datasets and Benchmarks Track
Global Convergence of Federated Learning for Mixed Regression Lili Su, Jiaming Xu, Pengkun Yang
Main Conference Track
BayesPCN: A Continually Learnable Predictive Coding Associative Memory Jinsoo Yoo, Frank Wood
Main Conference Track
Optimizing Data Collection for Machine Learning Rafid Mahmood, James Lucas, Jose M. Alvarez, Sanja Fidler, Marc Law
Main Conference Track
DP-PCA: Statistically Optimal and Differentially Private PCA Xiyang Liu, Weihao Kong, Prateek Jain, Sewoong Oh
Main Conference Track
Semantic Probabilistic Layers for Neuro-Symbolic Learning Kareem Ahmed, Stefano Teso, Kai-Wei Chang, Guy Van den Broeck, Antonio Vergari
Main Conference Track
Adapting to Online Label Shift with Provable Guarantees Yong Bai, Yu-Jie Zhang, Peng Zhao, Masashi Sugiyama, Zhi-Hua Zhou
Main Conference Track
CAGroup3D: Class-Aware Grouping for 3D Object Detection on Point Clouds Haiyang Wang, Lihe Ding, Shaocong Dong, Shaoshuai Shi, Aoxue Li, Jianan Li, Zhenguo Li, Liwei Wang
Main Conference Track
Revisiting Injective Attacks on Recommender Systems Haoyang LI, Shimin DI, Lei Chen
Main Conference Track
Learning-based Motion Planning in Dynamic Environments Using GNNs and Temporal Encoding Ruipeng Zhang, Chenning Yu, Jingkai Chen, Chuchu Fan, Sicun Gao
Main Conference Track
An empirical analysis of compute-optimal large language model training Jordan Hoffmann, Sebastian Borgeaud, Arthur Mensch, Elena Buchatskaya, Trevor Cai, Eliza Rutherford, Diego de Las Casas, Lisa Anne Hendricks, Johannes Welbl, Aidan Clark, Thomas Hennigan, Eric Noland, Katherine Millican, George van den Driessche, Bogdan Damoc, Aurelia Guy, Simon Osindero, Karén Simonyan, Erich Elsen, Oriol Vinyals, Jack Rae, Laurent Sifre
Main Conference Track
Robust Imitation via Mirror Descent Inverse Reinforcement Learning Dong-Sig Han, Hyunseo Kim, Hyundo Lee, JeHwan Ryu, Byoung-Tak Zhang
Main Conference Track
Characterizing Datapoints via Second-Split Forgetting Pratyush Maini, Saurabh Garg, Zachary Lipton, J. Zico Kolter
Main Conference Track
VoiceBlock: Privacy through Real-Time Adversarial Attacks with Audio-to-Audio Models Patrick O'Reilly, Andreas Bugler, Keshav Bhandari, Max Morrison, Bryan Pardo
Main Conference Track
A Theoretical View on Sparsely Activated Networks Cenk Baykal, Nishanth Dikkala, Rina Panigrahy, Cyrus Rashtchian, Xin Wang
Main Conference Track
Invariance Learning based on Label Hierarchy Shoji Toyota, Kenji Fukumizu
Main Conference Track
Effects of Data Geometry in Early Deep Learning Saket Tiwari, George Konidaris
Main Conference Track
When to Intervene: Learning Optimal Intervention Policies for Critical Events Niranjan Damera Venkata, Chiranjib Bhattacharyya
Main Conference Track
Draft-and-Revise: Effective Image Generation with Contextual RQ-Transformer Doyup Lee, Chiheon Kim, Saehoon Kim, Minsu Cho, WOOK SHIN HAN
Main Conference Track
Finite-Sample Maximum Likelihood Estimation of Location Shivam Gupta, Jasper Lee, ecprice, Paul Valiant
Main Conference Track
GENIE: Higher-Order Denoising Diffusion Solvers Tim Dockhorn, Arash Vahdat, Karsten Kreis
Main Conference Track
Provably Adversarially Robust Detection of Out-of-Distribution Data (Almost) for Free Alexander Meinke, Julian Bitterwolf, Matthias Hein
Main Conference Track
Efficient Graph Similarity Computation with Alignment Regularization Wei Zhuo, Guang Tan
Main Conference Track
Tsetlin Machine for Solving Contextual Bandit Problems Raihan Seraj, Jivitesh Sharma, Ole-Christoffer Granmo
Main Conference Track
Prune and distill: similar reformatting of image information along rat visual cortex and deep neural networks Paolo Muratore, Sina Tafazoli, Eugenio Piasini, Alessandro Laio, Davide Zoccolan
Main Conference Track
Graph Scattering beyond Wavelet Shackles Christian Koke, Gitta Kutyniok
Main Conference Track
Matryoshka Representation Learning Aditya Kusupati, Gantavya Bhatt, Aniket Rege, Matthew Wallingford, Aditya Sinha, Vivek Ramanujan, William Howard-Snyder, Kaifeng Chen, Sham Kakade, Prateek Jain, Ali Farhadi
Main Conference Track
Off-Policy Evaluation with Deficient Support Using Side Information Nicolò Felicioni, Maurizio Ferrari Dacrema, Marcello Restelli, Paolo Cremonesi
Main Conference Track
The Nature of Temporal Difference Errors in Multi-step Distributional Reinforcement Learning Yunhao Tang, Remi Munos, Mark Rowland, Bernardo Avila Pires, Will Dabney, Marc Bellemare
Main Conference Track
GraphDE: A Generative Framework for Debiased Learning and Out-of-Distribution Detection on Graphs Zenan Li, Qitian Wu, Fan Nie, Junchi Yan
Main Conference Track
Expectation-Maximization Contrastive Learning for Compact Video-and-Language Representations Peng Jin, Jinfa Huang, Fenglin Liu, Xian Wu, Shen Ge, Guoli Song, David Clifton, Jie Chen
Main Conference Track
Accelerating Sparse Convolution with Column Vector-Wise Sparsity Yijun Tan, Kai Han, Kang Zhao, Xianzhi Yu, Zidong Du, Yunji Chen, Yunhe Wang, Jun Yao
Main Conference Track
GPT3.int8(): 8-bit Matrix Multiplication for Transformers at Scale Tim Dettmers, Mike Lewis, Younes Belkada, Luke Zettlemoyer
Main Conference Track
Posterior Refinement Improves Sample Efficiency in Bayesian Neural Networks Agustinus Kristiadi, Runa Eschenhagen, Philipp Hennig
Main Conference Track
Micro and Macro Level Graph Modeling for Graph Variational Auto-Encoders Kiarash Zahirnia, Oliver Schulte, Parmis Naddaf, Ke Li
Main Conference Track
Spectral Bias Outside the Training Set for Deep Networks in the Kernel Regime Benjamin Bowman, Guido F. Montufar
Main Conference Track
The Unreliability of Explanations in Few-shot Prompting for Textual Reasoning Xi Ye, Greg Durrett
Main Conference Track
Self-Similarity Priors: Neural Collages as Differentiable Fractal Representations Michael Poli, Winnie Xu, Stefano Massaroli, Chenlin Meng, Kuno Kim, Stefano Ermon
Main Conference Track
Scalable Multi-agent Covering Option Discovery based on Kronecker Graphs Jiayu Chen, Jingdi Chen, Tian Lan, Vaneet Aggarwal
Main Conference Track
An Algorithm for Learning Switched Linear Dynamics from Data Guillaume Berger, Monal Narasimhamurthy, Kandai Watanabe, Morteza Lahijanian, Sriram Sankaranarayanan
Main Conference Track
LECO: Learnable Episodic Count for Task-Specific Intrinsic Reward Daejin Jo, Sungwoong Kim, Daniel Nam, Taehwan Kwon, Seungeun Rho, Jongmin Kim, Donghoon Lee
Main Conference Track
Generalised Implicit Neural Representations Daniele Grattarola, Pierre Vandergheynst
Main Conference Track
EZNAS: Evolving Zero-Cost Proxies For Neural Architecture Scoring Yash Akhauri, Juan Munoz, Nilesh Jain, Ravishankar Iyer
Main Conference Track
Personalized Federated Learning towards Communication Efficiency, Robustness and Fairness Shiyun Lin, Yuze Han, Xiang Li, Zhihua Zhang
Main Conference Track
Local Linear Convergence of Gradient Methods for Subspace Optimization via Strict Complementarity Ron Fisher, Dan Garber
Main Conference Track
Joint Learning of 2D-3D Weakly Supervised Semantic Segmentation Hyeokjun Kweon, Kuk-Jin Yoon
Main Conference Track
RNNs of RNNs: Recursive Construction of Stable Assemblies of Recurrent Neural Networks Leo Kozachkov, Michaela Ennis, Jean-Jacques Slotine
Main Conference Track
Training Spiking Neural Networks with Event-driven Backpropagation Yaoyu Zhu, Zhaofei Yu, Wei Fang, Xiaodong Xie, Tiejun Huang, Timothée Masquelier
Main Conference Track
Trade-off between Payoff and Model Rewards in Shapley-Fair Collaborative Machine Learning Quoc Phong Nguyen, Bryan Kian Hsiang Low, Patrick Jaillet
Main Conference Track
Efficient Non-Parametric Optimizer Search for Diverse Tasks Ruochen Wang, Yuanhao Xiong, Minhao Cheng, Cho-Jui Hsieh
Main Conference Track
DualCoOp: Fast Adaptation to Multi-Label Recognition with Limited Annotations Ximeng Sun, Ping Hu, Kate Saenko
Main Conference Track
What Can Transformers Learn In-Context? A Case Study of Simple Function Classes Shivam Garg, Dimitris Tsipras, Percy Liang, Gregory Valiant
Main Conference Track
Towards Robust Blind Face Restoration with Codebook Lookup Transformer Shangchen Zhou, Kelvin Chan, Chongyi Li, Chen Change Loy
Main Conference Track
Few-Shot Continual Active Learning by a Robot Ali Ayub, Carter Fendley
Main Conference Track
Learning Generalized Policy Automata for Relational Stochastic Shortest Path Problems Rushang Karia, Rashmeet Kaur Nayyar, Siddharth Srivastava
Main Conference Track
A Stochastic Linearized Augmented Lagrangian Method for Decentralized Bilevel Optimization Songtao Lu, Siliang Zeng, Xiaodong Cui, Mark Squillante, Lior Horesh, Brian Kingsbury, Jia Liu, Mingyi Hong
Main Conference Track
Boosting the Performance of Generic Deep Neural Network Frameworks with Log-supermodular CRFs Hao Xiong, Yangxiao Lu, Nicholas Ruozzi
Main Conference Track
Don't Roll the Dice, Ask Twice: The Two-Query Distortion of Matching Problems and Beyond Georgios Amanatidis, Georgios Birmpas, Aris Filos-Ratsikas, Alexandros Voudouris
Main Conference Track
On the Effect of Pre-training for Transformer in Different Modality on Offline Reinforcement Learning Shiro Takagi
Main Conference Track
Look where you look! Saliency-guided Q-networks for generalization in visual Reinforcement Learning David Bertoin, Adil Zouitine, Mehdi Zouitine, Emmanuel Rachelson
Main Conference Track
Information-Theoretic Safe Exploration with Gaussian Processes Alessandro Bottero, Carlos Luis, Julia Vinogradska, Felix Berkenkamp, Jan R Peters
Main Conference Track
On the consistent estimation of optimal Receiver Operating Characteristic (ROC) curve Renxiong Liu, Yunzhang Zhu
Main Conference Track
Online Algorithms for the Santa Claus Problem Max Springer, MohammadTaghi Hajiaghayi, Debmalya Panigrahi, Mohammad Khani
Main Conference Track
Instance-based Learning for Knowledge Base Completion Wanyun Cui, Xingran Chen
Main Conference Track
Decomposable Non-Smooth Convex Optimization with Nearly-Linear Gradient Oracle Complexity Sally Dong, Haotian Jiang, Yin Tat Lee, Swati Padmanabhan, Guanghao Ye
Main Conference Track
On Optimal Learning Under Targeted Data Poisoning Steve Hanneke, Amin Karbasi, Mohammad Mahmoody, Idan Mehalel, Shay Moran
Main Conference Track
Generalized Laplacian Eigenmaps Hao Zhu, Piotr Koniusz
Main Conference Track
OGC: Unsupervised 3D Object Segmentation from Rigid Dynamics of Point Clouds Ziyang Song, Bo Yang
Main Conference Track
Look More but Care Less in Video Recognition Yitian Zhang, Yue Bai, Huan Wang, Yi Xu, Yun Fu
Main Conference Track
Transferring Pre-trained Multimodal Representations with Cross-modal Similarity Matching Byoungjip Kim, Sungik Choi, Dasol Hwang, Moontae Lee, Honglak Lee
Main Conference Track
Get More at Once: Alternating Sparse Training with Gradient Correction Li Yang, Jian Meng, Jae-sun Seo, Deliang Fan
Main Conference Track
BLOX: Macro Neural Architecture Search Benchmark and Algorithms Thomas Chau, Łukasz Dudziak, Hongkai Wen, Nicholas Lane, Mohamed Abdelfattah
Datasets and Benchmarks Track
Does Self-supervised Learning Really Improve Reinforcement Learning from Pixels? Xiang Li, Jinghuan Shang, Srijan Das, Michael Ryoo
Main Conference Track
TCT: Convexifying Federated Learning using Bootstrapped Neural Tangent Kernels Yaodong Yu, Alexander Wei, Sai Praneeth Karimireddy, Yi Ma, Michael I. Jordan
Main Conference Track
Graph Coloring via Neural Networks for Haplotype Assembly and Viral Quasispecies Reconstruction Hansheng Xue, Vaibhav Rajan, Yu Lin
Main Conference Track
Active Learning of Classifiers with Label and Seed Queries Marco Bressan, Nicolò Cesa-Bianchi, Silvio Lattanzi, Andrea Paudice, Maximilian Thiessen
Main Conference Track
TANGO: Text-driven Photorealistic and Robust 3D Stylization via Lighting Decomposition Yongwei Chen, Rui Chen, Jiabao Lei, Yabin Zhang, Kui Jia
Main Conference Track
Analyzing Lottery Ticket Hypothesis from PAC-Bayesian Theory Perspective Keitaro Sakamoto, Issei Sato
Main Conference Track
Make Sharpness-Aware Minimization Stronger: A Sparsified Perturbation Approach Peng Mi, Li Shen, Tianhe Ren, Yiyi Zhou, Xiaoshuai Sun, Rongrong Ji, Dacheng Tao
Main Conference Track
From Gradient Flow on Population Loss to Learning with Stochastic Gradient Descent Christopher M De Sa, Satyen Kale, Jason Lee, Ayush Sekhari, Karthik Sridharan
Main Conference Track
Distributional Reinforcement Learning for Risk-Sensitive Policies Shiau Hong Lim, ILYAS MALIK
Main Conference Track
Text Classification with Born's Rule Emanuele Guidotti, Alfio Ferrara
Main Conference Track
Learning a Condensed Frame for Memory-Efficient Video Class-Incremental Learning Yixuan Pei, Zhiwu Qing, Jun CEN, Xiang Wang, Shiwei Zhang, Yaxiong Wang, Mingqian Tang, Nong Sang, Xueming Qian
Main Conference Track
Conformal Prediction with Temporal Quantile Adjustments Zhen Lin, Shubhendu Trivedi, Jimeng Sun
Main Conference Track
Learning Viewpoint-Agnostic Visual Representations by Recovering Tokens in 3D Space Jinghuan Shang, Srijan Das, Michael Ryoo
Main Conference Track
Certifying Some Distributional Fairness with Subpopulation Decomposition Mintong Kang, Linyi Li, Maurice Weber, Yang Liu, Ce Zhang, Bo Li
Main Conference Track
A Theoretical Understanding of Gradient Bias in Meta-Reinforcement Learning Bo Liu, Xidong Feng, Jie Ren, Luo Mai, Rui Zhu, Haifeng Zhang, Jun Wang, Yaodong Yang
Main Conference Track
Optimal Algorithms for Decentralized Stochastic Variational Inequalities Dmitry Kovalev, Aleksandr Beznosikov, Abdurakhmon Sadiev, Michael Persiianov, Peter Richtarik, Alexander Gasnikov
Main Conference Track
Mirror Descent Maximizes Generalized Margin and Can Be Implemented Efficiently Haoyuan Sun, Kwangjun Ahn, Christos Thrampoulidis, Navid Azizan
Main Conference Track
Adversarial Task Up-sampling for Meta-learning Yichen WU, Long-Kai Huang, Ying Wei
Main Conference Track
MAtt: A Manifold Attention Network for EEG Decoding Yue-Ting Pan, Jing-Lun Chou, Chun-Shu Wei
Main Conference Track
Geometry-aware Two-scale PIFu Representation for Human Reconstruction Zheng Dong, Ke Xu, Ziheng Duan, Hujun Bao, Weiwei Xu, Rynson Lau
Main Conference Track
Relational Proxies: Emergent Relationships as Fine-Grained Discriminators ABHRA CHAUDHURI, Massimiliano Mancini, Zeynep Akata, Anjan Dutta
Main Conference Track
Root Cause Analysis of Failures in Microservices through Causal Discovery Azam Ikram, Sarthak Chakraborty, Subrata Mitra, Shiv Saini, Saurabh Bagchi, Murat Kocaoglu
Main Conference Track
Anticipating Performativity by Predicting from Predictions Celestine Mendler-Dünner, Frances Ding, Yixin Wang
Main Conference Track
Falconn++: A Locality-sensitive Filtering Approach for Approximate Nearest Neighbor Search Ninh Pham, Tao Liu
Main Conference Track
Pre-Trained Language Models for Interactive Decision-Making Shuang Li, Xavier Puig, Chris Paxton, Yilun Du, Clinton Wang, Linxi Fan, Tao Chen, De-An Huang, Ekin Akyürek, Anima Anandkumar, Jacob Andreas, Igor Mordatch, Antonio Torralba, Yuke Zhu
Main Conference Track
Tight Analysis of Extra-gradient and Optimistic Gradient Methods For Nonconvex Minimax Problems Pouria Mahdavinia, Yuyang Deng, Haochuan Li, Mehrdad Mahdavi
Main Conference Track
Learning Generalizable Models for Vehicle Routing Problems via Knowledge Distillation Jieyi Bi, Yining Ma, Jiahai Wang, Zhiguang Cao, Jinbiao Chen, Yuan Sun, Yeow Meng Chee
Main Conference Track
Large-scale Optimization of Partial AUC in a Range of False Positive Rates Yao Yao, Qihang Lin, Tianbao Yang
Main Conference Track
The Burer-Monteiro SDP method can fail even above the Barvinok-Pataki bound Liam O'Carroll, Vaidehi Srinivas, Aravindan Vijayaraghavan
Main Conference Track
MinVIS: A Minimal Video Instance Segmentation Framework without Video-based Training De-An Huang, Zhiding Yu, Anima Anandkumar
Main Conference Track
Supported Policy Optimization for Offline Reinforcement Learning Jialong Wu, Haixu Wu, Zihan Qiu, Jianmin Wang, Mingsheng Long
Main Conference Track
Infinite Recommendation Networks: A Data-Centric Approach Noveen Sachdeva, Mehak Dhaliwal, Carole-Jean Wu, Julian J. Mcauley
Main Conference Track
DDXPlus: A New Dataset For Automatic Medical Diagnosis Arsene Fansi Tchango, Rishab Goel, Zhi Wen, Julien Martel, Joumana Ghosn
Datasets and Benchmarks Track
Clipped Stochastic Methods for Variational Inequalities with Heavy-Tailed Noise Eduard Gorbunov, Marina Danilova, David Dobre, Pavel Dvurechenskii, Alexander Gasnikov, Gauthier Gidel
Main Conference Track
A Unified Sequence Interface for Vision Tasks Ting Chen, Saurabh Saxena, Lala Li, Tsung-Yi Lin, David J Fleet, Geoffrey E. Hinton
Main Conference Track
Expected Frequency Matrices of Elections: Computation, Geometry, and Preference Learning Niclas Boehmer, Robert Bredereck, Edith Elkind, Piotr Faliszewski, Stanisław Szufa
Main Conference Track
GMMSeg: Gaussian Mixture based Generative Semantic Segmentation Models Chen Liang, Wenguan Wang, Jiaxu Miao, Yi Yang
Main Conference Track
Understanding and Extending Subgraph GNNs by Rethinking Their Symmetries Fabrizio Frasca, Beatrice Bevilacqua, Michael Bronstein, Haggai Maron
Main Conference Track
Parametrically Retargetable Decision-Makers Tend To Seek Power Alex Turner, Prasad Tadepalli
Main Conference Track
CageNeRF: Cage-based Neural Radiance Field for Generalized 3D Deformation and Animation Yicong Peng, Yichao Yan, Shengqi Liu, Yuhao Cheng, Shanyan Guan, Bowen Pan, Guangtao Zhai, Xiaokang Yang
Main Conference Track
Meta-Query-Net: Resolving Purity-Informativeness Dilemma in Open-set Active Learning Dongmin Park, Yooju Shin, Jihwan Bang, Youngjun Lee, Hwanjun Song, Jae-Gil Lee
Main Conference Track
Dance of SNN and ANN: Solving binding problem by combining spike timing and reconstructive attention Hao Zheng, Hui Lin, Rong Zhao, Luping Shi
Main Conference Track
Unsupervised Learning for Combinatorial Optimization with Principled Objective Relaxation Haoyu Peter Wang, Nan Wu, Hang Yang, Cong Hao, Pan Li
Main Conference Track
PAC-Bayes Compression Bounds So Tight That They Can Explain Generalization Sanae Lotfi, Marc Finzi, Sanyam Kapoor, Andres Potapczynski, Micah Goldblum, Andrew G Wilson
Main Conference Track
BagFlip: A Certified Defense Against Data Poisoning Yuhao Zhang, Aws Albarghouthi, Loris D'Antoni
Main Conference Track
Data augmentation for efficient learning from parametric experts Alexandre Galashov, Josh S Merel, Nicolas Heess
Main Conference Track
Symmetry-induced Disentanglement on Graphs Giangiacomo Mercatali, Andre Freitas, Vikas Garg
Main Conference Track
Conformal Off-Policy Prediction in Contextual Bandits Muhammad Faaiz Taufiq, Jean-Francois Ton, Rob Cornish, Yee Whye Teh, Arnaud Doucet
Main Conference Track
Black-Box Generalization: Stability of Zeroth-Order Learning Konstantinos Nikolakakis, Farzin Haddadpour, Dionysis Kalogerias, Amin Karbasi
Main Conference Track
First Contact: Unsupervised Human-Machine Co-Adaptation via Mutual Information Maximization Siddharth Reddy, Sergey Levine, Anca Dragan
Main Conference Track
HyperMiner: Topic Taxonomy Mining with Hyperbolic Embedding Yi.shi Xu, Dongsheng Wang, Bo Chen, Ruiying Lu, Zhibin Duan, Mingyuan Zhou
Main Conference Track
Visual Concepts Tokenization Tao Yang, Yuwang Wang, Yan Lu, Nanning Zheng
Main Conference Track
ZooD: Exploiting Model Zoo for Out-of-Distribution Generalization Qishi Dong, Awais Muhammad, Fengwei Zhou, Chuanlong Xie, Tianyang Hu, Yongxin Yang, Sung-Ho Bae, Zhenguo Li
Main Conference Track
Nearly-Tight Bounds for Testing Histogram Distributions Clément L Canonne, Ilias Diakonikolas, Daniel Kane, Sihan Liu
Main Conference Track
TGEA 2.0: A Large-Scale Diagnostically Annotated Dataset with Benchmark Tasks for Text Generation of Pretrained Language Models Huibin Ge, Xiaohu Zhao, Chuang Liu, Yulong Zeng, Qun Liu, Deyi Xiong
Datasets and Benchmarks Track
Quantifying Statistical Significance of Neural Network-based Image Segmentation by Selective Inference Vo Nguyen Le Duy, Shogo Iwazaki, Ichiro Takeuchi
Main Conference Track
A Differentially Private Linear-Time fPTAS for the Minimum Enclosing Ball Problem Bar Mahpud, Or Sheffet
Main Conference Track
BEER: Fast $O(1/T)$ Rate for Decentralized Nonconvex Optimization with Communication Compression Haoyu Zhao, Boyue Li, Zhize Li, Peter Richtarik, Yuejie Chi
Main Conference Track
Autoregressive Search Engines: Generating Substrings as Document Identifiers Michele Bevilacqua, Giuseppe Ottaviano, Patrick Lewis, Scott Yih, Sebastian Riedel, Fabio Petroni
Main Conference Track
Sampling with Riemannian Hamiltonian Monte Carlo in a Constrained Space Yunbum Kook, Yin-Tat Lee, Ruoqi Shen, Santosh Vempala
Main Conference Track
Are All Losses Created Equal: A Neural Collapse Perspective Jinxin Zhou, Chong You, Xiao Li, Kangning Liu, Sheng Liu, Qing Qu, Zhihui Zhu
Main Conference Track
Fair Ranking with Noisy Protected Attributes Anay Mehrotra, Nisheeth Vishnoi
Main Conference Track
Social-Inverse: Inverse Decision-making of Social Contagion Management with Task Migrations Guangmo Tong
Main Conference Track
Provable Benefit of Multitask Representation Learning in Reinforcement Learning Yuan Cheng, Songtao Feng, Jing Yang, Hong Zhang, Yingbin Liang
Main Conference Track
Modeling Human Exploration Through Resource-Rational Reinforcement Learning Marcel Binz, Eric Schulz
Main Conference Track
Generating Long Videos of Dynamic Scenes Tim Brooks, Janne Hellsten, Miika Aittala, Ting-Chun Wang, Timo Aila, Jaakko Lehtinen, Ming-Yu Liu, Alexei Efros, Tero Karras
Main Conference Track
DigGAN: Discriminator gradIent Gap Regularization for GAN Training with Limited Data Tiantian Fang, Ruoyu Sun, Alex Schwing
Main Conference Track
ORIENT: Submodular Mutual Information Measures for Data Subset Selection under Distribution Shift Athresh Karanam, Krishnateja Killamsetty, Harsha Kokel, Rishabh Iyer
Main Conference Track
The BigScience ROOTS Corpus: A 1.6TB Composite Multilingual Dataset Hugo Laurençon, Lucile Saulnier, Thomas Wang, Christopher Akiki, Albert Villanova del Moral, Teven Le Scao, Leandro Von Werra, Chenghao Mou, Eduardo González Ponferrada, Huu Nguyen, Jörg Frohberg, Mario Šaško, Quentin Lhoest, Angelina McMillan-Major, Gerard Dupont, Stella Biderman, Anna Rogers, Loubna Ben allal, Francesco De Toni, Giada Pistilli, Olivier Nguyen, Somaieh Nikpoor, Maraim Masoud, Pierre Colombo, Javier de la Rosa, Paulo Villegas, Tristan Thrush, Shayne Longpre, Sebastian Nagel, Leon Weber, Manuel Muñoz, Jian Zhu, Daniel Van Strien, Zaid Alyafeai, Khalid Almubarak, Minh Chien Vu, Itziar Gonzalez-Dios, Aitor Soroa, Kyle Lo, Manan Dey, Pedro Ortiz Suarez, Aaron Gokaslan, Shamik Bose, David Adelani, Long Phan, Hieu Tran, Ian Yu, Suhas Pai, Jenny Chim, Violette Lepercq, Suzana Ilic, Margaret Mitchell, Sasha Alexandra Luccioni, Yacine Jernite
Datasets and Benchmarks Track
Module-Aware Optimization for Auxiliary Learning Hong Chen, Xin Wang, Yue Liu, Yuwei Zhou, Chaoyu Guan, Wenwu Zhu
Main Conference Track
GET3D: A Generative Model of High Quality 3D Textured Shapes Learned from Images Jun Gao, Tianchang Shen, Zian Wang, Wenzheng Chen, Kangxue Yin, Daiqing Li, Or Litany, Zan Gojcic, Sanja Fidler
Main Conference Track
BYOL-Explore: Exploration by Bootstrapped Prediction Zhaohan Guo, Shantanu Thakoor, Miruna Pislar, Bernardo Avila Pires, Florent Altché, Corentin Tallec, Alaa Saade, Daniele Calandriello, Jean-Bastien Grill, Yunhao Tang, Michal Valko, Remi Munos, Mohammad Gheshlaghi Azar, Bilal Piot
Main Conference Track
SizeShiftReg: a Regularization Method for Improving Size-Generalization in Graph Neural Networks Davide Buffelli, Pietro Lió, Fabio Vandin
Main Conference Track
On the Effectiveness of Lipschitz-Driven Rehearsal in Continual Learning Lorenzo Bonicelli, Matteo Boschini, Angelo Porrello, Concetto Spampinato, SIMONE CALDERARA
Main Conference Track
Interpreting Operation Selection in Differentiable Architecture Search: A Perspective from Influence-Directed Explanations Miao Zhang, Wei Huang, Bin Yang
Main Conference Track
Collaborative Learning of Discrete Distributions under Heterogeneity and Communication Constraints Xinmeng Huang, Donghwan Lee, Edgar Dobriban, Hamed Hassani
Main Conference Track
On the Stability and Scalability of Node Perturbation Learning Naoki Hiratani, Yash Mehta, Timothy Lillicrap, Peter E Latham
Main Conference Track
Unsupervised Learning of Group Invariant and Equivariant Representations Robin Winter, Marco Bertolini, Tuan Le, Frank Noe, Djork-Arné Clevert
Main Conference Track
Factored Adaptation for Non-Stationary Reinforcement Learning Fan Feng, Biwei Huang, Kun Zhang, Sara Magliacane
Main Conference Track
MAgNet: Mesh Agnostic Neural PDE Solver Oussama Boussif, Yoshua Bengio, Loubna Benabbou, Dan Assouline
Main Conference Track
TarGF: Learning Target Gradient Field to Rearrange Objects without Explicit Goal Specification Mingdong Wu, Fangwei Zhong, Yulong Xia, Hao Dong
Main Conference Track
Learning to Compare Nodes in Branch and Bound with Graph Neural Networks Abdel Ghani Labassi, Didier Chetelat, Andrea Lodi
Main Conference Track
Teach Less, Learn More: On the Undistillable Classes in Knowledge Distillation Yichen Zhu, Ning Liu, Zhiyuan Xu, Xin Liu, Weibin Meng, Louis Wang, Zhicai Ou, Jian Tang
Main Conference Track
GAGA: Deciphering Age-path of Generalized Self-paced Regularizer Xingyu Qu, Diyang Li, Xiaohan Zhao, Bin Gu
Main Conference Track
ATD: Augmenting CP Tensor Decomposition by Self Supervision Chaoqi Yang, Cheng Qian, Navjot Singh, Cao (Danica) Xiao, M Westover, Edgar Solomonik, Jimeng Sun
Main Conference Track
Towards Learning Universal Hyperparameter Optimizers with Transformers Yutian Chen, Xingyou Song, Chansoo Lee, Zi Wang, Richard Zhang, David Dohan, Kazuya Kawakami, Greg Kochanski, Arnaud Doucet, Marc'Aurelio Ranzato, Sagi Perel, Nando de Freitas
Main Conference Track
Learning to Reconstruct Missing Data from Spatiotemporal Graphs with Sparse Observations Ivan Marisca, Andrea Cini, Cesare Alippi
Main Conference Track
Robust Graph Structure Learning via Multiple Statistical Tests Yaohua Wang, Fangyi Zhang, Ming Lin, Senzhang Wang, Xiuyu Sun, Rong Jin
Main Conference Track
Peripheral Vision Transformer Juhong Min, Yucheng Zhao, Chong Luo, Minsu Cho
Main Conference Track
Maximum Common Subgraph Guided Graph Retrieval: Late and Early Interaction Networks Indradyumna Roy, Soumen Chakrabarti, Abir De
Main Conference Track
Differentially Private Learning with Margin Guarantees Raef Bassily, Mehryar Mohri, Ananda Theertha Suresh
Main Conference Track
ADBench: Anomaly Detection Benchmark Songqiao Han, Xiyang Hu, Hailiang Huang, Minqi Jiang, Yue Zhao
Datasets and Benchmarks Track
GLIF: A Unified Gated Leaky Integrate-and-Fire Neuron for Spiking Neural Networks Xingting Yao, Fanrong Li, Zitao Mo, Jian Cheng
Main Conference Track
HSDF: Hybrid Sign and Distance Field for Modeling Surfaces with Arbitrary Topologies Li Wang, jie Yang, Weikai Chen, Xiaoxu Meng, Bo Yang, Jintao Li, Lin Gao
Main Conference Track
Inverse Game Theory for Stackelberg Games: the Blessing of Bounded Rationality Jibang Wu, Weiran Shen, Fei Fang, Haifeng Xu
Main Conference Track
When Privacy Meets Partial Information: A Refined Analysis of Differentially Private Bandits Achraf Azize, Debabrota Basu
Main Conference Track
Robust Reinforcement Learning using Offline Data Kishan Panaganti, Zaiyan Xu, Dileep Kalathil, Mohammad Ghavamzadeh
Main Conference Track
Compositional generalization through abstract representations in human and artificial neural networks Takuya Ito, Tim Klinger, Doug Schultz, John Murray, Michael Cole, Mattia Rigotti
Main Conference Track
Self-Consistent Dynamical Field Theory of Kernel Evolution in Wide Neural Networks Blake Bordelon, Cengiz Pehlevan
Main Conference Track
Provably expressive temporal graph networks Amauri Souza, Diego Mesquita, Samuel Kaski, Vikas Garg
Main Conference Track
Maximum Likelihood Training of Implicit Nonlinear Diffusion Model Dongjun Kim, Byeonghu Na, Se Jung Kwon, Dongsoo Lee, Wanmo Kang, Il-chul Moon
Main Conference Track
First is Better Than Last for Language Data Influence Chih-Kuan Yeh, Ankur Taly, Mukund Sundararajan, Frederick Liu, Pradeep K. Ravikumar
Main Conference Track
Deep Combinatorial Aggregation Yuesong Shen, Daniel Cremers
Main Conference Track
Efficient coding, channel capacity, and the emergence of retinal mosaics Na Young Jun, Greg Field, John C. Pearson
Main Conference Track
TA-GATES: An Encoding Scheme for Neural Network Architectures Xuefei Ning, Zixuan Zhou, Junbo Zhao, Tianchen Zhao, Yiping Deng, Changcheng Tang, Shuang Liang, Huazhong Yang, Yu Wang
Main Conference Track
ZSON: Zero-Shot Object-Goal Navigation using Multimodal Goal Embeddings Arjun Majumdar, Gunjan Aggarwal, Bhavika Devnani, Judy Hoffman, Dhruv Batra
Main Conference Track
Autoformalization with Large Language Models Yuhuai Wu, Albert Qiaochu Jiang, Wenda Li, Markus Rabe, Charles Staats, Mateja Jamnik, Christian Szegedy
Main Conference Track
Model-based Lifelong Reinforcement Learning with Bayesian Exploration Haotian Fu, Shangqun Yu, Michael L. Littman, George Konidaris
Main Conference Track
On Efficient Online Imitation Learning via Classification Yichen Li, Chicheng Zhang
Main Conference Track
Let Images Give You More: Point Cloud Cross-Modal Training for Shape Analysis Xu Yan, Heshen Zhan, Chaoda Zheng, Jiantao Gao, Ruimao Zhang, Shuguang Cui, Zhen Li
Main Conference Track
On Robust Multiclass Learnability Jingyuan Xu, Weiwei Liu
Main Conference Track
Debiased Self-Training for Semi-Supervised Learning Baixu Chen, Junguang Jiang, Ximei Wang, Pengfei Wan, Jianmin Wang, Mingsheng Long
Main Conference Track
Rethinking Individual Global Max in Cooperative Multi-Agent Reinforcement Learning Yitian Hong, Yaochu Jin, Yang Tang
Main Conference Track
Archimedes Meets Privacy: On Privately Estimating Quantiles in High Dimensions Under Minimal Assumptions Omri Ben-Eliezer, Dan Mikulincer, Ilias Zadik
Main Conference Track
Uncovering the Structural Fairness in Graph Contrastive Learning Ruijia Wang, Xiao Wang, Chuan Shi, Le Song
Main Conference Track
Estimation of Entropy in Constant Space with Improved Sample Complexity Maryam Aliakbarpour, Andrew McGregor, Jelani Nelson, Erik Waingarten
Main Conference Track
Average Sensitivity of Euclidean k-Clustering Yuichi Yoshida, Shinji Ito
Main Conference Track
Multi-block-Single-probe Variance Reduced Estimator for Coupled Compositional Optimization Wei Jiang, Gang Li, Yibo Wang, Lijun Zhang, Tianbao Yang
Main Conference Track
Differentially Private Online-to-batch for Smooth Losses Qinzi Zhang, Hoang Tran, Ashok Cutkosky
Main Conference Track
Weak-shot Semantic Segmentation via Dual Similarity Transfer Junjie Chen, Li Niu, Siyuan Zhou, Jianlou Si, Chen Qian, Liqing Zhang
Main Conference Track
A Multi-Task Benchmark for Korean Legal Language Understanding and Judgement Prediction Wonseok Hwang, Dongjun Lee, Kyoungyeon Cho, Hanuhl Lee, Minjoon Seo
Datasets and Benchmarks Track
Synergy-of-Experts: Collaborate to Improve Adversarial Robustness Sen Cui, Jingfeng ZHANG, Jian Liang, Bo Han, Masashi Sugiyama, Changshui Zhang
Main Conference Track
Improved Fine-Tuning by Better Leveraging Pre-Training Data Ziquan Liu, Yi Xu, Yuanhong Xu, Qi Qian, Hao Li, Xiangyang Ji, Antoni B. Chan, Rong Jin
Main Conference Track
Transferring Fairness under Distribution Shifts via Fair Consistency Regularization Bang An, Zora Che, Mucong Ding, Furong Huang
Main Conference Track
OpenOOD: Benchmarking Generalized Out-of-Distribution Detection Jingkang Yang, Pengyun Wang, Dejian Zou, Zitang Zhou, Kunyuan Ding, WENXUAN PENG, Haoqi Wang, Guangyao Chen, Bo Li, Yiyou Sun, Xuefeng Du, Kaiyang Zhou, Wayne Zhang, Dan Hendrycks, Yixuan Li, Ziwei Liu
Datasets and Benchmarks Track
Two-layer neural network on infinite dimensional data: global optimization guarantee in the mean-field regime Naoki Nishikawa, Taiji Suzuki, Atsushi Nitanda, Denny Wu
Main Conference Track
KSD Aggregated Goodness-of-fit Test Antonin Schrab, Benjamin Guedj, Arthur Gretton
Main Conference Track
Efficient Risk-Averse Reinforcement Learning Ido Greenberg, Yinlam Chow, Mohammad Ghavamzadeh, Shie Mannor
Main Conference Track
D^2NeRF: Self-Supervised Decoupling of Dynamic and Static Objects from a Monocular Video Tianhao Wu, Fangcheng Zhong, Andrea Tagliasacchi, Forrester Cole, Cengiz Oztireli
Main Conference Track
On the Effective Number of Linear Regions in Shallow Univariate ReLU Networks: Convergence Guarantees and Implicit Bias Itay Safran, Gal Vardi, Jason Lee
Main Conference Track
Robust $\phi$-Divergence MDPs Chin Pang Ho, Marek Petrik, Wolfram Wiesemann
Main Conference Track
Object Representations as Fixed Points: Training Iterative Refinement Algorithms with Implicit Differentiation Michael Chang, Tom Griffiths, Sergey Levine
Main Conference Track
Benefits of Additive Noise in Composing Classes with Bounded Capacity Alireza Fathollah Pour, Hassan Ashtiani
Main Conference Track
Multi-Objective Deep Learning with Adaptive Reference Vectors Weiyu Chen, James T. Kwok
Main Conference Track
Towards Hard-pose Virtual Try-on via 3D-aware Global Correspondence Learning Zaiyu Huang, Hanhui Li, Zhenyu Xie, Michael Kampffmeyer, qingling Cai, Xiaodan Liang
Main Conference Track
Pushing the limits of fairness impossibility: Who's the fairest of them all? Brian Hsu, Rahul Mazumder, Preetam Nandy, Kinjal Basu
Main Conference Track
Recall Distortion in Neural Network Pruning and the Undecayed Pruning Algorithm Aidan Good, Jiaqi Lin, Xin Yu, Hannah Sieg, Mikey Fergurson, Shandian Zhe, Jerzy Wieczorek, Thiago Serra
Main Conference Track
Generating multivariate time series with COmmon Source CoordInated GAN (COSCI-GAN) Ali Seyfi, Jean-Francois Rajotte, Raymond Ng
Main Conference Track
ConfounderGAN: Protecting Image Data Privacy with Causal Confounder Qi Tian, Kun Kuang, Kelu Jiang, Furui Liu, Zhihua Wang, Fei Wu
Main Conference Track
Global Convergence of Direct Policy Search for State-Feedback $\mathcal{H}_\infty$ Robust Control: A Revisit of Nonsmooth Synthesis with Goldstein Subdifferential Xingang Guo, Bin Hu
Main Conference Track
In What Ways Are Deep Neural Networks Invariant and How Should We Measure This? Henry Kvinge, Tegan Emerson, Grayson Jorgenson, Scott Vasquez, Tim Doster, Jesse Lew
Main Conference Track
Optimal Weak to Strong Learning Kasper Green Larsen, Martin Ritzert
Main Conference Track
A Neural Pre-Conditioning Active Learning Algorithm to Reduce Label Complexity Seo Taek Kong, Soomin Jeon, Dongbin Na, Jaewon Lee, Hong-Seok Lee, Kyu-Hwan Jung
Main Conference Track
AnoShift: A Distribution Shift Benchmark for Unsupervised Anomaly Detection Marius Dragoi, Elena Burceanu, Emanuela Haller, Andrei Manolache, Florin Brad
Datasets and Benchmarks Track
Grounding Aleatoric Uncertainty for Unsupervised Environment Design Minqi Jiang, Michael Dennis, Jack Parker-Holder, Andrei Lupu, Heinrich Küttler, Edward Grefenstette, Tim Rocktäschel, Jakob Foerster
Main Conference Track
PROSPECT: Labeled Tandem Mass Spectrometry Dataset for Machine Learning in Proteomics Omar Shouman, Wassim Gabriel, Victor-George Giurcoiu, Vitor Sternlicht, Mathias Wilhelm
Datasets and Benchmarks Track
VLMo: Unified Vision-Language Pre-Training with Mixture-of-Modality-Experts Hangbo Bao, Wenhui Wang, Li Dong, Qiang Liu, Owais Khan Mohammed, Kriti Aggarwal, Subhojit Som, Songhao Piao, Furu Wei
Main Conference Track
Hub-Pathway: Transfer Learning from A Hub of Pre-trained Models Yang Shu, Zhangjie Cao, Ziyang Zhang, Jianmin Wang, Mingsheng Long
Main Conference Track
Towards Better Evaluation for Dynamic Link Prediction Farimah Poursafaei, Shenyang Huang, Kellin Pelrine, Reihaneh Rabbany
Datasets and Benchmarks Track
Coarse-to-Fine Vision-Language Pre-training with Fusion in the Backbone Zi-Yi Dou, Aishwarya Kamath, Zhe Gan, Pengchuan Zhang, Jianfeng Wang, Linjie Li, Zicheng Liu, Ce Liu, Yann LeCun, Nanyun Peng, Jianfeng Gao, Lijuan Wang
Main Conference Track
On the Discrimination Risk of Mean Aggregation Feature Imputation in Graphs Arjun Subramonian, Kai-Wei Chang, Yizhou Sun
Main Conference Track
VRL3: A Data-Driven Framework for Visual Deep Reinforcement Learning Che Wang, Xufang Luo, Keith Ross, Dongsheng Li
Main Conference Track
Efficient and Effective Optimal Transport-Based Biclustering Chakib Fettal, lazhar labiod, Mohamed NADIF
Main Conference Track
Unifying and Boosting Gradient-Based Training-Free Neural Architecture Search YAO SHU, Zhongxiang Dai, Zhaoxuan Wu, Bryan Kian Hsiang Low
Main Conference Track
Hyperbolic Embedding Inference for Structured Multi-Label Prediction Bo Xiong, Michael Cochez, Mojtaba Nayyeri, Steffen Staab
Main Conference Track
Approximate Value Equivalence Christopher Grimm, Andre Barreto, Satinder P. Singh
Main Conference Track
The Power and Limitation of Pretraining-Finetuning for Linear Regression under Covariate Shift Jingfeng Wu, Difan Zou, Vladimir Braverman, Quanquan Gu, Sham Kakade
Main Conference Track
Rank Diminishing in Deep Neural Networks Ruili Feng, Kecheng Zheng, Yukun Huang, Deli Zhao, Michael I. Jordan, Zheng-Jun Zha
Main Conference Track
Single-pass Streaming Lower Bounds for Multi-armed Bandits Exploration with Instance-sensitive Sample Complexity Sepehr Assadi, Chen Wang
Main Conference Track
Optimistic Tree Searches for Combinatorial Black-Box Optimization Cedric Malherbe, Antoine Grosnit, Rasul Tutunov, Haitham Bou Ammar, Jun Wang
Main Conference Track
Robust Feature-Level Adversaries are Interpretability Tools Stephen Casper, Max Nadeau, Dylan Hadfield-Menell, Gabriel Kreiman
Main Conference Track
A Unified Convergence Theorem for Stochastic Optimization Methods Xiao Li, Andre Milzarek
Main Conference Track
New Definitions and Evaluations for Saliency Methods: Staying Intrinsic, Complete and Sound Arushi Gupta, Nikunj Saunshi, Dingli Yu, Kaifeng Lyu, Sanjeev Arora
Main Conference Track
Exponential Separations in Symmetric Neural Networks Aaron Zweig, Joan Bruna
Main Conference Track
Randomized Message-Interception Smoothing: Gray-box Certificates for Graph Neural Networks Yan Scholten, Jan Schuchardt, Simon Geisler, Aleksandar Bojchevski, Stephan Günnemann
Main Conference Track
Oscillatory Tracking of Continuous Attractor Neural Networks Account for Phase Precession and Procession of Hippocampal Place Cells Tianhao Chu, Zilong Ji, Junfeng Zuo, Wenhao Zhang, Tiejun Huang, Yuanyuan Mi, Si Wu
Main Conference Track
Finding and Listing Front-door Adjustment Sets Hyunchai Jeong, Jin Tian, Elias Bareinboim
Main Conference Track
MorphTE: Injecting Morphology in Tensorized Embeddings Guobing Gan, Peng Zhang, Sunzhu Li, Xiuqing Lu, Benyou Wang
Main Conference Track
Active Learning with Safety Constraints Romain Camilleri, Andrew Wagenmaker, Jamie H Morgenstern, Lalit Jain, Kevin G. Jamieson
Main Conference Track
Is one annotation enough? - A data-centric image classification benchmark for noisy and ambiguous label estimation Lars Schmarje, Vasco Grossmann, Claudius Zelenka, Sabine Dippel, Rainer Kiko, Mariusz Oszust, Matti Pastell, Jenny Stracke, Anna Valros, Nina Volkmann, Reinhard Koch
Datasets and Benchmarks Track
Sobolev Acceleration and Statistical Optimality for Learning Elliptic Equations via Gradient Descent Yiping Lu, Jose Blanchet, Lexing Ying
Main Conference Track
Block-Recurrent Transformers DeLesley Hutchins, Imanol Schlag, Yuhuai Wu, Ethan Dyer, Behnam Neyshabur
Main Conference Track
Learning Two-Player Markov Games: Neural Function Approximation and Correlated Equilibrium Chris Junchi Li, Dongruo Zhou, Quanquan Gu, Michael I. Jordan
Main Conference Track
Dense Interspecies Face Embedding Sejong Yang, Subin Jeon, Seonghyeon Nam, Seon Joo Kim
Main Conference Track
Efficient Scheduling of Data Augmentation for Deep Reinforcement Learning Byungchan Ko, Jungseul Ok
Main Conference Track
Mix and Reason: Reasoning over Semantic Topology with Data Mixing for Domain Generalization Chaoqi Chen, Luyao Tang, Feng Liu, Gangming Zhao, Yue Huang, Yizhou Yu
Main Conference Track
Personalized Online Federated Learning with Multiple Kernels Pouya M. Ghari, Yanning Shen
Main Conference Track
Point Transformer V2: Grouped Vector Attention and Partition-based Pooling Xiaoyang Wu, Yixing Lao, Li Jiang, Xihui Liu, Hengshuang Zhao
Main Conference Track
Learning Concept Credible Models for Mitigating Shortcuts Jiaxuan Wang, Sarah Jabbour, Maggie Makar, Michael Sjoding, Jenna Wiens
Main Conference Track
Neural Approximation of Graph Topological Features Zuoyu Yan, Tengfei Ma, Liangcai Gao, Zhi Tang, Yusu Wang, Chao Chen
Main Conference Track
MOVE: Unsupervised Movable Object Segmentation and Detection Adam Bielski, Paolo Favaro
Main Conference Track
FreGAN: Exploiting Frequency Components for Training GANs under Limited Data mengping yang, Zhe Wang, Ziqiu Chi, Yanbing Zhang
Main Conference Track
LBD: Decouple Relevance and Observation for Individual-Level Unbiased Learning to Rank Mouxiang Chen, Chenghao Liu, Zemin Liu, Jianling Sun
Main Conference Track
MetricFormer: A Unified Perspective of Correlation Exploring in Similarity Learning Jiexi Yan, Erkun Yang, Cheng Deng, Heng Huang
Main Conference Track
Toward a realistic model of speech processing in the brain with self-supervised learning Juliette MILLET, Charlotte Caucheteux, pierre orhan, Yves Boubenec, Alexandre Gramfort, Ewan Dunbar, Christophe Pallier, Jean-Remi King
Main Conference Track
Distributed Inverse Constrained Reinforcement Learning for Multi-agent Systems Shicheng Liu, Minghui Zhu
Main Conference Track
Collaborative Decision Making Using Action Suggestions Dylan Asmar, Mykel J Kochenderfer
Main Conference Track
Near-Optimal Regret for Adversarial MDP with Delayed Bandit Feedback Tiancheng Jin, Tal Lancewicki, Haipeng Luo, Yishay Mansour, Aviv Rosenberg
Main Conference Track
Provably sample-efficient RL with side information about latent dynamics Yao Liu, Dipendra Misra, Miro Dudik, Robert E. Schapire
Main Conference Track
Optimal Gradient Sliding and its Application to Optimal Distributed Optimization Under Similarity Dmitry Kovalev, Aleksandr Beznosikov, Ekaterina Borodich, Alexander Gasnikov, Gesualdo Scutari
Main Conference Track
Universally Expressive Communication in Multi-Agent Reinforcement Learning Matthew Morris, Thomas D Barrett, Arnu Pretorius
Main Conference Track
Fast Stochastic Composite Minimization and an Accelerated Frank-Wolfe Algorithm under Parallelization Benjamin Dubois-Taine, Francis R. Bach, Quentin Berthet, Adrien Taylor
Main Conference Track
Multi-Granularity Cross-modal Alignment for Generalized Medical Visual Representation Learning Fuying Wang, Yuyin Zhou, Shujun WANG, Varut Vardhanabhuti, Lequan Yu
Main Conference Track
Learning Robust Rule Representations for Abstract Reasoning via Internal Inferences Wenbo Zhang, likai tang, Site Mo, Xianggen Liu, Sen Song
Main Conference Track
Turning the Tables: Biased, Imbalanced, Dynamic Tabular Datasets for ML Evaluation Sérgio Jesus, José Pombal, Duarte Alves, André Cruz, Pedro Saleiro, Rita Ribeiro, João Gama, Pedro Bizarro
Datasets and Benchmarks Track
DropCov: A Simple yet Effective Method for Improving Deep Architectures Qilong Wang, Mingze Gao, Zhaolin Zhang, Jiangtao Xie, Peihua Li, Qinghua Hu
Main Conference Track
A Unifying Framework for Online Optimization with Long-Term Constraints Matteo Castiglioni, Andrea Celli, Alberto Marchesi, Giulia Romano, Nicola Gatti
Main Conference Track
The least-control principle for local learning at equilibrium Alexander Meulemans, Nicolas Zucchet, Seijin Kobayashi, Johannes von Oswald, João Sacramento
Main Conference Track
Optimizing Relevance Maps of Vision Transformers Improves Robustness Hila Chefer, Idan Schwartz, Lior Wolf
Main Conference Track
Stability and Generalization of Kernel Clustering: from Single Kernel to Multiple Kernel Weixuan Liang, Xinwang Liu, Yong Liu, sihang zhou, Jun-Jie Huang, Siwei Wang, Jiyuan Liu, Yi Zhang, En Zhu
Main Conference Track
Deep Ensembles Work, But Are They Necessary? Taiga Abe, Estefany Kelly Buchanan, Geoff Pleiss, Richard S. Zemel, John P. Cunningham
Main Conference Track
VICE: Variational Interpretable Concept Embeddings Lukas Muttenthaler, Charles Y Zheng, Patrick McClure, Robert A Vandermeulen, Martin N Hebart, Francisco Pereira
Main Conference Track
Random Normalization Aggregation for Adversarial Defense Minjing Dong, Xinghao Chen, Yunhe Wang, Chang Xu
Main Conference Track
Distributionally Robust Optimization with Data Geometry Jiashuo Liu, Jiayun Wu, Bo Li, Peng Cui
Main Conference Track
Near-Optimal Correlation Clustering with Privacy Vincent Cohen-Addad, Chenglin Fan, Silvio Lattanzi, Slobodan Mitrovic, Ashkan Norouzi-Fard, Nikos Parotsidis, Jakub M Tarnawski
Main Conference Track
Knowledge Distillation from A Stronger Teacher Tao Huang, Shan You, Fei Wang, Chen Qian, Chang Xu
Main Conference Track
Optimal Transport of Classifiers to Fairness Maarten Buyl, Tijl De Bie
Main Conference Track
Rethinking the compositionality of point clouds through regularization in the hyperbolic space Antonio Montanaro, Diego Valsesia, Enrico Magli
Main Conference Track
ReCo: Retrieve and Co-segment for Zero-shot Transfer Gyungin Shin, Weidi Xie, Samuel Albanie
Main Conference Track
Monocular Dynamic View Synthesis: A Reality Check Hang Gao, Ruilong Li, Shubham Tulsiani, Bryan Russell, Angjoo Kanazawa
Main Conference Track
Bridging the Gap between Object and Image-level Representations for Open-Vocabulary Detection Hanoona Bangalath, Muhammad Maaz, Muhammad Uzair Khattak, Salman H Khan, Fahad Shahbaz Khan
Main Conference Track
A Simple and Optimal Policy Design for Online Learning with Safety against Heavy-tailed Risk David Simchi-Levi, Zeyu Zheng, Feng Zhu
Main Conference Track
A Boosting Approach to Reinforcement Learning Nataly Brukhim, Elad Hazan, Karan Singh
Main Conference Track
Relaxing Equivariance Constraints with Non-stationary Continuous Filters Tycho van der Ouderaa, David W. Romero, Mark van der Wilk
Main Conference Track
The Franz-Parisi Criterion and Computational Trade-offs in High Dimensional Statistics Afonso S Bandeira, Ahmed El Alaoui, Samuel Hopkins, Tselil Schramm, Alexander S Wein, Ilias Zadik
Main Conference Track
Robust Neural Posterior Estimation and Statistical Model Criticism Daniel Ward, Patrick Cannon, Mark Beaumont, Matteo Fasiolo, Sebastian Schmon
Main Conference Track
Why do We Need Large Batchsizes in Contrastive Learning? A Gradient-Bias Perspective Changyou Chen, Jianyi Zhang, Yi Xu, Liqun Chen, Jiali Duan, Yiran Chen, Son Tran, Belinda Zeng, Trishul Chilimbi
Main Conference Track
Randomized Channel Shuffling: Minimal-Overhead Backdoor Attack Detection without Clean Datasets Ruisi Cai, Zhenyu Zhang, Tianlong Chen, Xiaohan Chen, Zhangyang Wang
Main Conference Track
Structural Analysis of Branch-and-Cut and the Learnability of Gomory Mixed Integer Cuts Maria-Florina F Balcan, Siddharth Prasad, Tuomas Sandholm, Ellen Vitercik
Main Conference Track
Finite-Time Last-Iterate Convergence for Learning in Multi-Player Games Yang Cai, Argyris Oikonomou, Weiqiang Zheng
Main Conference Track
When are Local Queries Useful for Robust Learning? Pascale Gourdeau, Varun Kanade, Marta Kwiatkowska, James Worrell
Main Conference Track
SPoVT: Semantic-Prototype Variational Transformer for Dense Point Cloud Semantic Completion Sheng Yu Huang, Hao-Yu Hsu, Frank Wang
Main Conference Track
Improving Intrinsic Exploration with Language Abstractions Jesse Mu, Victor Zhong, Roberta Raileanu, Minqi Jiang, Noah Goodman, Tim Rocktäschel, Edward Grefenstette
Main Conference Track
The trade-offs of model size in large recommendation models : 100GB to 10MB Criteo-tb DLRM model Aditya Desai, Anshumali Shrivastava
Main Conference Track
Near-Optimal Goal-Oriented Reinforcement Learning in Non-Stationary Environments Liyu Chen, Haipeng Luo
Main Conference Track
A Unified Framework for Deep Symbolic Regression Mikel Landajuela, Chak Shing Lee, Jiachen Yang, Ruben Glatt, Claudio P Santiago, Ignacio Aravena, Terrell Mundhenk, Garrett Mulcahy, Brenden K Petersen
Main Conference Track
VoxGRAF: Fast 3D-Aware Image Synthesis with Sparse Voxel Grids Katja Schwarz, Axel Sauer, Michael Niemeyer, Yiyi Liao, Andreas Geiger
Main Conference Track
Sparse Hypergraph Community Detection Thresholds in Stochastic Block Model Erchuan Zhang, David Suter, Giang Truong, Syed Zulqarnain Gilani
Main Conference Track
Understanding Non-linearity in Graph Neural Networks from the Bayesian-Inference Perspective Rongzhe Wei, Haoteng YIN, Junteng Jia, Austin R Benson, Pan Li
Main Conference Track
Explainable Reinforcement Learning via Model Transforms Mira Finkelstein, Nitsan levy, Lucy Liu, Yoav Kolumbus, David C. Parkes, Jeffrey S Rosenschein, Sarah Keren
Main Conference Track
Real-Valued Backpropagation is Unsuitable for Complex-Valued Neural Networks Zhi-Hao Tan, Yi Xie, Yuan Jiang, Zhi-Hua Zhou
Main Conference Track
Learning dynamics of deep linear networks with multiple pathways Jianghong Shi, Eric Shea-Brown, Michael Buice
Main Conference Track
Self-Supervised Aggregation of Diverse Experts for Test-Agnostic Long-Tailed Recognition Yifan Zhang, Bryan Hooi, Lanqing Hong, Jiashi Feng
Main Conference Track
Self-Supervised Learning via Maximum Entropy Coding Xin Liu, Zhongdao Wang, Ya-Li Li, Shengjin Wang
Main Conference Track
A Practical, Progressively-Expressive GNN Lingxiao Zhao, Neil Shah, Leman Akoglu
Main Conference Track
On Learning Fairness and Accuracy on Multiple Subgroups Changjian Shui, Gezheng Xu, Qi CHEN, Jiaqi Li, Charles X. Ling, Tal Arbel, Boyu Wang, Christian Gagné
Main Conference Track
Adv-Attribute: Inconspicuous and Transferable Adversarial Attack on Face Recognition Shuai Jia, Bangjie Yin, Taiping Yao, Shouhong Ding, Chunhua Shen, Xiaokang Yang, Chao Ma
Main Conference Track
Understanding Aesthetics with Language: A Photo Critique Dataset for Aesthetic Assessment Daniel Vera Nieto, Luigi Celona, Clara Fernandez Labrador
Datasets and Benchmarks Track
Structuring Representations Using Group Invariants Mehran Shakerinava, Arnab Kumar Mondal, Siamak Ravanbakhsh
Main Conference Track
Black-box coreset variational inference Dionysis Manousakas, Hippolyt Ritter, Theofanis Karaletsos
Main Conference Track
Distilling Representations from GAN Generator via Squeeze and Span Yu Yang, Xiaotian Cheng, Chang Liu, Hakan Bilen, Xiangyang Ji
Main Conference Track
A Quantitative Geometric Approach to Neural-Network Smoothness Zi Wang, Gautam Prakriya, Somesh Jha
Main Conference Track
AutoMTL: A Programming Framework for Automating Efficient Multi-Task Learning Lijun Zhang, Xiao Liu, Hui Guan
Main Conference Track
Log-Concave and Multivariate Canonical Noise Distributions for Differential Privacy Jordan Awan, Jinshuo Dong
Main Conference Track
On the generalization of learning algorithms that do not converge Nisha Chandramoorthy, Andreas Loukas, Khashayar Gatmiry, Stefanie Jegelka
Main Conference Track
PALMER: Perception - Action Loop with Memory for Long-Horizon Planning Onur Beker, Mohammad Mohammadi, Amir Zamir
Main Conference Track
Leveraging Factored Action Spaces for Efficient Offline Reinforcement Learning in Healthcare Shengpu Tang, Maggie Makar, Michael Sjoding, Finale Doshi-Velez, Jenna Wiens
Main Conference Track
Visual correspondence-based explanations improve AI robustness and human-AI team accuracy Mohammad Reza Taesiri, Giang Nguyen, Anh Nguyen
Main Conference Track
Invariance-Aware Randomized Smoothing Certificates Jan Schuchardt, Stephan Günnemann
Main Conference Track
On Image Segmentation With Noisy Labels: Characterization and Volume Properties of the Optimal Solutions to Accuracy and Dice Marcus Nordstrom, Henrik Hult, Fredrik Löfman, Jonas Söderberg
Main Conference Track
Blessing of Depth in Linear Regression: Deeper Models Have Flatter Landscape Around the True Solution Jianhao Ma, Salar Fattahi
Main Conference Track
Fairness Reprogramming Guanhua Zhang, Yihua Zhang, Yang Zhang, Wenqi Fan, Qing Li, Sijia Liu, Shiyu Chang
Main Conference Track
WeightedSHAP: analyzing and improving Shapley based feature attributions Yongchan Kwon, James Y Zou
Main Conference Track
Temporal Effective Batch Normalization in Spiking Neural Networks Chaoteng Duan, Jianhao Ding, Shiyan Chen, Zhaofei Yu, Tiejun Huang
Main Conference Track
Remember the Past: Distilling Datasets into Addressable Memories for Neural Networks Zhiwei Deng, Olga Russakovsky
Main Conference Track
Robustness Analysis of Video-Language Models Against Visual and Language Perturbations Madeline Schiappa, Shruti Vyas, Hamid Palangi, Yogesh Rawat, Vibhav Vineet
Datasets and Benchmarks Track
Hyperbolic Feature Augmentation via Distribution Estimation and Infinite Sampling on Manifolds Zhi Gao, Yuwei Wu, Yunde Jia, Mehrtash Harandi
Main Conference Track
PatchComplete: Learning Multi-Resolution Patch Priors for 3D Shape Completion on Unseen Categories Yuchen Rao, Yinyu Nie, Angela Dai
Main Conference Track
Q-ViT: Accurate and Fully Quantized Low-bit Vision Transformer Yanjing Li, Sheng Xu, Baochang Zhang, Xianbin Cao, Peng Gao, Guodong Guo
Main Conference Track
Enhancing Safe Exploration Using Safety State Augmentation Aivar Sootla, Alexander Cowen-Rivers, Jun Wang, Haitham Bou Ammar
Main Conference Track
Unsupervised Reinforcement Learning with Contrastive Intrinsic Control Michael Laskin, Hao Liu, Xue Bin Peng, Denis Yarats, Aravind Rajeswaran, Pieter Abbeel
Main Conference Track
Distributed Online Convex Optimization with Compressed Communication Zhipeng Tu, Xi Wang, Yiguang Hong, Lei Wang, Deming Yuan, Guodong Shi
Main Conference Track
Local Latent Space Bayesian Optimization over Structured Inputs Natalie Maus, Haydn Jones, Juston Moore, Matt J Kusner, John Bradshaw, Jacob Gardner
Main Conference Track
Graph Neural Network Bandits Parnian Kassraie, Andreas Krause, Ilija Bogunovic
Main Conference Track
Concrete Score Matching: Generalized Score Matching for Discrete Data Chenlin Meng, Kristy Choi, Jiaming Song, Stefano Ermon
Main Conference Track
Regularized Gradient Descent Ascent for Two-Player Zero-Sum Markov Games Sihan Zeng, Thinh Doan, Justin Romberg
Main Conference Track
Chefs' Random Tables: Non-Trigonometric Random Features Valerii Likhosherstov, Krzysztof M Choromanski, Kumar Avinava Dubey, Frederick Liu, Tamas Sarlos, Adrian Weller
Main Conference Track
CS-Shapley: Class-wise Shapley Values for Data Valuation in Classification Stephanie Schoch, Haifeng Xu, Yangfeng Ji
Main Conference Track
Factuality Enhanced Language Models for Open-Ended Text Generation Nayeon Lee, Wei Ping, Peng Xu, Mostofa Patwary, Pascale N Fung, Mohammad Shoeybi, Bryan Catanzaro
Main Conference Track
On the Representation Collapse of Sparse Mixture of Experts Zewen Chi, Li Dong, Shaohan Huang, Damai Dai, Shuming Ma, Barun Patra, Saksham Singhal, Payal Bajaj, XIA SONG, Xian-Ling Mao, Heyan Huang, Furu Wei
Main Conference Track
Nearly Optimal Algorithms for Linear Contextual Bandits with Adversarial Corruptions Jiafan He, Dongruo Zhou, Tong Zhang, Quanquan Gu
Main Conference Track
Implicit Bias of Gradient Descent on Reparametrized Models: On Equivalence to Mirror Descent Zhiyuan Li, Tianhao Wang, Jason Lee, Sanjeev Arora
Main Conference Track
HYPRO: A Hybridly Normalized Probabilistic Model for Long-Horizon Prediction of Event Sequences Siqiao Xue, Xiaoming Shi, James Zhang, Hongyuan Mei
Main Conference Track
Towards Understanding Grokking: An Effective Theory of Representation Learning Ziming Liu, Ouail Kitouni, Niklas S Nolte, Eric Michaud, Max Tegmark, Mike Williams
Main Conference Track
Asymptotic Behaviors of Projected Stochastic Approximation: A Jump Diffusion Perspective Jiadong Liang, Yuze Han, Xiang Li, Zhihua Zhang
Main Conference Track
Towards Practical Few-shot Query Sets: Transductive Minimum Description Length Inference Ségolène Martin, Malik Boudiaf, Emilie Chouzenoux, Jean-Christophe Pesquet, Ismail Ayed
Main Conference Track
Understanding the Generalization Benefit of Normalization Layers: Sharpness Reduction Kaifeng Lyu, Zhiyuan Li, Sanjeev Arora
Main Conference Track
Learning Manifold Dimensions with Conditional Variational Autoencoders Yijia Zheng, Tong He, Yixuan Qiu, David P Wipf
Main Conference Track
Multi-modal Grouping Network for Weakly-Supervised Audio-Visual Video Parsing Shentong Mo, Yapeng Tian
Main Conference Track
Optimal-er Auctions through Attention Dmitry Ivanov, Iskander Safiulin, Igor Filippov, Ksenia Balabaeva
Main Conference Track
Bootstrapped Transformer for Offline Reinforcement Learning Kerong Wang, Hanye Zhao, Xufang Luo, Kan Ren, Weinan Zhang, Dongsheng Li
Main Conference Track
How to talk so AI will learn: Instructions, descriptions, and autonomy Theodore Sumers, Robert Hawkins, Mark K Ho, Tom Griffiths, Dylan Hadfield-Menell
Main Conference Track
Learning on the Edge: Online Learning with Stochastic Feedback Graphs Emmanuel Esposito, Federico Fusco, Dirk van der Hoeven, Nicolò Cesa-Bianchi
Main Conference Track
Globally Gated Deep Linear Networks Qianyi Li, Haim Sompolinsky
Main Conference Track
Markov Chain Score Ascent: A Unifying Framework of Variational Inference with Markovian Gradients Kyurae Kim, Jisu Oh, Jacob Gardner, Adji Bousso Dieng, Hongseok Kim
Main Conference Track
Cache-Augmented Inbatch Importance Resampling for Training Recommender Retriever Jin Chen, Defu Lian, Yucheng Li, Baoyun Wang, Kai Zheng, Enhong Chen
Main Conference Track
Doubly Robust Counterfactual Classification Kwangho Kim, Edward Kennedy, Jose Zubizarreta
Main Conference Track
Rethinking Value Function Learning for Generalization in Reinforcement Learning Seungyong Moon, JunYeong Lee, Hyun Oh Song
Main Conference Track
Improving Certified Robustness via Statistical Learning with Logical Reasoning Zhuolin Yang, Zhikuan Zhao, Boxin Wang, Jiawei Zhang, Linyi Li, Hengzhi Pei, Bojan Karlaš, Ji Liu, Heng Guo, Ce Zhang, Bo Li
Main Conference Track
Transformer-based Working Memory for Multiagent Reinforcement Learning with Action Parsing Yaodong Yang, Guangyong Chen, Weixun Wang, Xiaotian Hao, Jianye Hao, Pheng-Ann Heng
Main Conference Track
Recruitment Strategies That Take a Chance Gregory Kehne, Ariel D Procaccia, Jingyan Wang
Main Conference Track
Fully Convolutional One-Stage 3D Object Detection on LiDAR Range Images Zhi Tian, Xiangxiang Chu, Xiaoming Wang, Xiaolin Wei, Chunhua Shen
Main Conference Track
Understanding Robust Learning through the Lens of Representation Similarities Christian Cianfarani, Arjun Nitin Bhagoji, Vikash Sehwag, Ben Zhao, Heather Zheng, Prateek Mittal
Main Conference Track
Chartalist: Labeled Graph Datasets for UTXO and Account-based Blockchains Kiarash Shamsi, Friedhelm Victor, Murat Kantarcioglu, Yulia Gel, Cuneyt G Akcora
Datasets and Benchmarks Track
Multi-Instance Causal Representation Learning for Instance Label Prediction and Out-of-Distribution Generalization Weijia Zhang, Xuanhui Zhang, hanwen deng, Min-Ling Zhang
Main Conference Track
PerfectDou: Dominating DouDizhu with Perfect Information Distillation Guan Yang, Minghuan Liu, Weijun Hong, Weinan Zhang, Fei Fang, Guangjun Zeng, Yue Lin
Main Conference Track
On the Double Descent of Random Features Models Trained with SGD Fanghui Liu, Johan Suykens, Volkan Cevher
Main Conference Track
SALSA: Attacking Lattice Cryptography with Transformers Emily Wenger, Mingjie Chen, Francois Charton, Kristin E. Lauter
Main Conference Track
Variable-rate hierarchical CPC leads to acoustic unit discovery in speech Santiago Cuervo, Adrian Lancucki, Ricard Marxer, Paweł Rychlikowski, Jan K Chorowski
Main Conference Track
Learning to Attack Federated Learning: A Model-based Reinforcement Learning Attack Framework Henger Li, Xiaolin Sun, Zizhan Zheng
Main Conference Track
Learning Neural Set Functions Under the Optimal Subset Oracle Zijing Ou, Tingyang Xu, Qinliang Su, Yingzhen Li, Peilin Zhao, Yatao Bian
Main Conference Track
A Near-Optimal Best-of-Both-Worlds Algorithm for Online Learning with Feedback Graphs Chloé Rouyer, Dirk van der Hoeven, Nicolò Cesa-Bianchi, Yevgeny Seldin
Main Conference Track
Optimal Query Complexities for Dynamic Trace Estimation David Woodruff, Fred Zhang, Richard Zhang
Main Conference Track
Learning from Stochastically Revealed Preference John Birge, Xiaocheng Li, Chunlin Sun
Main Conference Track
Mutual Information Divergence: A Unified Metric for Multimodal Generative Models Jin-Hwa Kim, Yunji Kim, Jiyoung Lee, Kang Min Yoo, Sang-Woo Lee
Main Conference Track
Delving into Out-of-Distribution Detection with Vision-Language Representations Yifei Ming, Ziyang Cai, Jiuxiang Gu, Yiyou Sun, Wei Li, Yixuan Li
Main Conference Track
OnePose++: Keypoint-Free One-Shot Object Pose Estimation without CAD Models Xingyi He, Jiaming Sun, Yuang Wang, Di Huang, Hujun Bao, Xiaowei Zhou
Main Conference Track
Confidence-based Reliable Learning under Dual Noises Peng Cui, Yang Yue, Zhijie Deng, Jun Zhu
Main Conference Track
Multitasking Models are Robust to Structural Failure: A Neural Model for Bilingual Cognitive Reserve Giannis Daras, Negin Raoof, Zoi Gkalitsiou, Alex Dimakis
Main Conference Track
Learning (Very) Simple Generative Models Is Hard Sitan Chen, Jerry Li, Yuanzhi Li
Main Conference Track
PEER: A Comprehensive and Multi-Task Benchmark for Protein Sequence Understanding Minghao Xu, Zuobai Zhang, Jiarui Lu, Zhaocheng Zhu, Yangtian Zhang, Ma Chang, Runcheng Liu, Jian Tang
Datasets and Benchmarks Track
Bring Your Own Algorithm for Optimal Differentially Private Stochastic Minimax Optimization Liang Zhang, Kiran K Thekumparampil, Sewoong Oh, Niao He
Main Conference Track
A Regret-Variance Trade-Off in Online Learning Dirk van der Hoeven, Nikita Zhivotovskiy, Nicolò Cesa-Bianchi
Main Conference Track
Alternating Mirror Descent for Constrained Min-Max Games Andre Wibisono, Molei Tao, Georgios Piliouras
Main Conference Track
Deep Counterfactual Estimation with Categorical Background Variables Edward De Brouwer
Main Conference Track
SnAKe: Bayesian Optimization with Pathwise Exploration Jose Pablo Folch, Shiqiang Zhang, Robert Lee, Behrang Shafei, David Walz, Calvin Tsay, Mark van der Wilk, Ruth Misener
Main Conference Track
Self-Supervised Learning with an Information Maximization Criterion Serdar Ozsoy, Shadi Hamdan, Sercan Arik, Deniz Yuret, Alper Erdogan
Main Conference Track
TwiBot-22: Towards Graph-Based Twitter Bot Detection Shangbin Feng, Zhaoxuan Tan, Herun Wan, Ningnan Wang, Zilong Chen, Binchi Zhang, Qinghua Zheng, Wenqian Zhang, Zhenyu Lei, Shujie Yang, Xinshun Feng, Qingyue Zhang, Hongrui Wang, Yuhan Liu, Yuyang Bai, Heng Wang, Zijian Cai, Yanbo Wang, Lijing Zheng, Zihan Ma, Jundong Li, Minnan Luo
Datasets and Benchmarks Track
Listen to Interpret: Post-hoc Interpretability for Audio Networks with NMF Jayneel Parekh, Sanjeel Parekh, Pavlo Mozharovskyi, Florence d'Alché-Buc, Gaël Richard
Main Conference Track
Model-based RL with Optimistic Posterior Sampling: Structural Conditions and Sample Complexity Alekh Agarwal, Tong Zhang
Main Conference Track
Deep Architecture Connectivity Matters for Its Convergence: A Fine-Grained Analysis Wuyang Chen, Wei Huang, Xinyu Gong, Boris Hanin, Zhangyang Wang
Main Conference Track
OrdinalCLIP: Learning Rank Prompts for Language-Guided Ordinal Regression Wanhua Li, Xiaoke Huang, Zheng Zhu, Yansong Tang, Xiu Li, Jie Zhou, Jiwen Lu
Main Conference Track
Kernel Memory Networks: A Unifying Framework for Memory Modeling Georgios Iatropoulos, Johanni Brea, Wulfram Gerstner
Main Conference Track
The First Optimal Acceleration of High-Order Methods in Smooth Convex Optimization Dmitry Kovalev, Alexander Gasnikov
Main Conference Track
CCCP is Frank-Wolfe in disguise Alp Yurtsever, Suvrit Sra
Main Conference Track
Uni[MASK]: Unified Inference in Sequential Decision Problems Micah Carroll, Orr Paradise, Jessy Lin, Raluca Georgescu, Mingfei Sun, David Bignell, Stephanie Milani, Katja Hofmann, Matthew Hausknecht, Anca Dragan, Sam Devlin
Main Conference Track
Efficient Active Learning with Abstention Yinglun Zhu, Robert Nowak
Main Conference Track
SInGE: Sparsity via Integrated Gradients Estimation of Neuron Relevance Edouard YVINEC, Arnaud Dapogny, Matthieu Cord, Kevin Bailly
Main Conference Track
On the Complexity of Adversarial Decision Making Dylan J Foster, Alexander Rakhlin, Ayush Sekhari, Karthik Sridharan
Main Conference Track
MoCapAct: A Multi-Task Dataset for Simulated Humanoid Control Nolan Wagener, Andrey Kolobov, Felipe Vieira Frujeri, Ricky Loynd, Ching-An Cheng, Matthew Hausknecht
Datasets and Benchmarks Track
On the Effectiveness of Persistent Homology Renata Turkes, Guido F. Montufar, Nina Otter
Main Conference Track
An Adaptive Deep RL Method for Non-Stationary Environments with Piecewise Stable Context Xiaoyu Chen, Xiangming Zhu, Yufeng Zheng, Pushi Zhang, Li Zhao, Wenxue Cheng, Peng CHENG, Yongqiang Xiong, Tao Qin, Jianyu Chen, Tie-Yan Liu
Main Conference Track
Expediting Large-Scale Vision Transformer for Dense Prediction without Fine-tuning WEICONG LIANG, YUHUI YUAN, Henghui Ding, Xiao Luo, Weihong Lin, Ding Jia, Zheng Zhang, Chao Zhang, Han Hu
Main Conference Track
Flowification: Everything is a normalizing flow Bálint Máté, Samuel Klein, Tobias Golling, François Fleuret
Main Conference Track
A time-resolved theory of information encoding in recurrent neural networks Rainer Engelken, Sven Goedeke
Main Conference Track
A Unified Analysis of Mixed Sample Data Augmentation: A Loss Function Perspective Chanwoo Park, Sangdoo Yun, Sanghyuk Chun
Main Conference Track
Recursive Reinforcement Learning Ernst Moritz Hahn, Mateo Perez, Sven Schewe, Fabio Somenzi, Ashutosh Trivedi, Dominik Wojtczak
Main Conference Track
Non-Linguistic Supervision for Contrastive Learning of Sentence Embeddings Yiren Jian, Chongyang Gao, Soroush Vosoughi
Main Conference Track
Towards Video Text Visual Question Answering: Benchmark and Baseline Minyi Zhao, Bingjia Li, Jie Wang, Wanqing Li, Wenjing Zhou, Lan Zhang, Shijie Xuyang, Zhihang Yu, Xinkun Yu, Guangze Li, Aobotao Dai, Shuigeng Zhou
Datasets and Benchmarks Track
4D Unsupervised Object Discovery Yuqi Wang, Yuntao Chen, ZHAO-XIANG ZHANG
Main Conference Track
Faster Linear Algebra for Distance Matrices Piotr Indyk, Sandeep Silwal
Main Conference Track
Contextual Bandits with Knapsacks for a Conversion Model Zhen LI, Gilles Stoltz
Main Conference Track
Contrastive Learning as Goal-Conditioned Reinforcement Learning Benjamin Eysenbach, Tianjun Zhang, Sergey Levine, Ruslan Salakhutdinov
Main Conference Track
The Pitfalls of Regularization in Off-Policy TD Learning Gaurav Manek, J. Zico Kolter
Main Conference Track
MCMAE: Masked Convolution Meets Masked Autoencoders Peng Gao, Teli Ma, Hongsheng Li, Ziyi Lin, Jifeng Dai, Yu Qiao
Main Conference Track
Robustness to Label Noise Depends on the Shape of the Noise Distribution Diane Oyen, Michal Kucer, Nicolas Hengartner, Har Simrat Singh
Main Conference Track
Fast Neural Kernel Embeddings for General Activations Insu Han, Amir Zandieh, Jaehoon Lee, Roman Novak, Lechao Xiao, Amin Karbasi
Main Conference Track
Deep invariant networks with differentiable augmentation layers Cédric ROMMEL, Thomas Moreau, Alexandre Gramfort
Main Conference Track
Factorized-FL: Personalized Federated Learning with Parameter Factorization & Similarity Matching Wonyong Jeong, Sung Ju Hwang
Main Conference Track
Reinforcement Learning with a Terminator Guy Tennenholtz, Nadav Merlis, Lior Shani, Shie Mannor, Uri Shalit, Gal Chechik, Assaf Hallak, Gal Dalal
Main Conference Track
How Transferable are Video Representations Based on Synthetic Data? Yo-whan Kim, Samarth Mishra, SouYoung Jin, Rameswar Panda, Hilde Kuehne, Leonid Karlinsky, Venkatesh Saligrama, Kate Saenko, Aude Oliva, Rogerio Feris
Datasets and Benchmarks Track
Sub-exponential time Sum-of-Squares lower bounds for Principal Components Analysis Aaron Potechin, Goutham Rajendran
Main Conference Track
A Multilabel Classification Framework for Approximate Nearest Neighbor Search Ville Hyvönen, Elias Jääsaari, Teemu Roos
Main Conference Track
Learnable Polyphase Sampling for Shift Invariant and Equivariant Convolutional Networks Renan A. Rojas-Gomez, Teck-Yian Lim, Alex Schwing, Minh Do, Raymond A. Yeh
Main Conference Track
Not All Bits have Equal Value: Heterogeneous Precisions via Trainable Noise Pedro Savarese, Xin Yuan, Yanjing Li, Michael Maire
Main Conference Track
Tensor Program Optimization with Probabilistic Programs Junru Shao, Xiyou Zhou, Siyuan Feng, Bohan Hou, Ruihang Lai, Hongyi Jin, Wuwei Lin, Masahiro Masuda, Cody Hao Yu, Tianqi Chen
Main Conference Track
Deep Generative Model for Periodic Graphs Shiyu Wang, Xiaojie Guo, Liang Zhao
Main Conference Track
Exploring the Limits of Domain-Adaptive Training for Detoxifying Large-Scale Language Models Boxin Wang, Wei Ping, Chaowei Xiao, Peng Xu, Mostofa Patwary, Mohammad Shoeybi, Bo Li, Anima Anandkumar, Bryan Catanzaro
Main Conference Track
Relational Reasoning via Set Transformers: Provable Efficiency and Applications to MARL Fengzhuo Zhang, Boyi Liu, Kaixin Wang, Vincent Tan, Zhuoran Yang, Zhaoran Wang
Main Conference Track
Missing Data Imputation and Acquisition with Deep Hierarchical Models and Hamiltonian Monte Carlo Ignacio Peis, Chao Ma, José Miguel Hernández-Lobato
Main Conference Track
Score-Based Generative Models Detect Manifolds Jakiw Pidstrigach
Main Conference Track
Distributionally Robust Optimization via Ball Oracle Acceleration Yair Carmon, Danielle Hausler
Main Conference Track
Palm up: Playing in the Latent Manifold for Unsupervised Pretraining Hao Liu, Tom Zahavy, Volodymyr Mnih, Satinder P. Singh
Main Conference Track
Fair Infinitesimal Jackknife: Mitigating the Influence of Biased Training Data Points Without Refitting Prasanna Sattigeri, Soumya Ghosh, Inkit Padhi, Pierre Dognin, Kush R Varshney
Main Conference Track
JAWS: Auditing Predictive Uncertainty Under Covariate Shift Drew Prinster, Anqi Liu, Suchi Saria
Main Conference Track
DNA: Proximal Policy Optimization with a Dual Network Architecture Matthew Aitchison, Penny Sweetser
Main Conference Track
Triangulation candidates for Bayesian optimization Robert B. Gramacy, Annie Sauer, Nathan Wycoff
Main Conference Track
Masked Autoencoders As Spatiotemporal Learners Christoph Feichtenhofer, haoqi fan, Yanghao Li, Kaiming He
Main Conference Track
PyramidCLIP: Hierarchical Feature Alignment for Vision-language Model Pretraining Yuting Gao, Jinfeng Liu, Zihan Xu, Jun Zhang, Ke Li, Rongrong Ji, Chunhua Shen
Main Conference Track
On the Parameterization and Initialization of Diagonal State Space Models Albert Gu, Karan Goel, Ankit Gupta, Christopher Ré
Main Conference Track
Implicit Regularization or Implicit Conditioning? Exact Risk Trajectories of SGD in High Dimensions Courtney Paquette, Elliot Paquette, Ben Adlam, Jeffrey Pennington
Main Conference Track
Extrapolative Continuous-time Bayesian Neural Network for Fast Training-free Test-time Adaptation Hengguan Huang, Xiangming Gu, Hao Wang, Chang Xiao, Hongfu Liu, Ye Wang
Main Conference Track
Global Convergence and Stability of Stochastic Gradient Descent Vivak Patel, Shushu Zhang, Bowen Tian
Main Conference Track
Trap and Replace: Defending Backdoor Attacks by Trapping Them into an Easy-to-Replace Subnetwork Haotao Wang, Junyuan Hong, Aston Zhang, Jiayu Zhou, Zhangyang Wang
Main Conference Track
Reinforcement Learning with Logarithmic Regret and Policy Switches Grigoris Velegkas, Zhuoran Yang, Amin Karbasi
Main Conference Track
Cluster and Aggregate: Face Recognition with Large Probe Set Minchul Kim, Feng Liu, Anil K Jain, Xiaoming Liu
Main Conference Track
GLIPv2: Unifying Localization and Vision-Language Understanding Haotian Zhang, Pengchuan Zhang, Xiaowei Hu, Yen-Chun Chen, Liunian Li, Xiyang Dai, Lijuan Wang, Lu Yuan, Jenq-Neng Hwang, Jianfeng Gao
Main Conference Track
Rethinking Alignment in Video Super-Resolution Transformers Shuwei Shi, Jinjin Gu, Liangbin Xie, Xintao Wang, Yujiu Yang, Chao Dong
Main Conference Track
Robustness in deep learning: The good (width), the bad (depth), and the ugly (initialization) Zhenyu Zhu, Fanghui Liu, Grigorios Chrysos, Volkan Cevher
Main Conference Track
Learning to Scaffold: Optimizing Model Explanations for Teaching Patrick Fernandes, Marcos Treviso, Danish Pruthi, André Martins, Graham Neubig
Main Conference Track
AutoLink: Self-supervised Learning of Human Skeletons and Object Outlines by Linking Keypoints Xingzhe He, Bastian Wandt, Helge Rhodin
Main Conference Track
Composite Feature Selection Using Deep Ensembles Fergus Imrie, Alexander Norcliffe, Pietro Lió, Mihaela van der Schaar
Main Conference Track
Scaling Multimodal Pre-Training via Cross-Modality Gradient Harmonization Junru Wu, Yi Liang, feng han, Hassan Akbari, Zhangyang Wang, Cong Yu
Main Conference Track
Bounded-Regret MPC via Perturbation Analysis: Prediction Error, Constraints, and Nonlinearity Yiheng Lin, Yang Hu, Guannan Qu, Tongxin Li, Adam Wierman
Main Conference Track
AniFaceGAN: Animatable 3D-Aware Face Image Generation for Video Avatars Yue Wu, Yu Deng, Jiaolong Yang, Fangyun Wei, Qifeng Chen, Xin Tong
Main Conference Track
Addressing Resource Scarcity across Sign Languages with Multilingual Pretraining and Unified-Vocabulary Datasets Gokul NC, Manideep Ladi, Sumit Negi, Prem Selvaraj, Pratyush Kumar, Mitesh Khapra
Datasets and Benchmarks Track
Detection and Localization of Changes in Conditional Distributions Lizhen Nie, Dan Nicolae
Main Conference Track
Refining Low-Resource Unsupervised Translation by Language Disentanglement of Multilingual Translation Model Xuan-Phi Nguyen, Shafiq Joty, Kui Wu, Ai Ti Aw
Main Conference Track
A Mean-Field Game Approach to Cloud Resource Management with Function Approximation Weichao Mao, Haoran Qiu, Chen Wang, Hubertus Franke, Zbigniew Kalbarczyk, Ravishankar Iyer, Tamer Basar
Main Conference Track
Regret Bounds for Risk-Sensitive Reinforcement Learning Osbert Bastani, Jason Yecheng Ma, Estelle Shen, Wanqiao Xu
Main Conference Track
BILCO: An Efficient Algorithm for Joint Alignment of Time Series Xuelong Mi, Mengfan Wang, Alex Chen, Jing-Xuan Lim, Yizhi Wang, Misha B Ahrens, Guoqiang Yu
Main Conference Track
Giving Feedback on Interactive Student Programs with Meta-Exploration Evan Liu, Moritz Stephan, Allen Nie, Chris Piech, Emma Brunskill, Chelsea Finn
Main Conference Track
Left Heavy Tails and the Effectiveness of the Policy and Value Networks in DNN-based best-first search for Sokoban Planning Dieqiao Feng, Carla P. Gomes, Bart Selman
Main Conference Track
Nonparametric Uncertainty Quantification for Single Deterministic Neural Network Nikita Kotelevskii, Aleksandr Artemenkov, Kirill Fedyanin, Fedor Noskov, Alexander Fishkov, Artem Shelmanov, Artem Vazhentsev, Aleksandr Petiushko, Maxim Panov
Main Conference Track
Decoupling Features in Hierarchical Propagation for Video Object Segmentation Zongxin Yang, Yi Yang
Main Conference Track
Computationally Efficient Horizon-Free Reinforcement Learning for Linear Mixture MDPs Dongruo Zhou, Quanquan Gu
Main Conference Track
Counterfactual harm Jonathan Richens, Rory Beard, Daniel H. Thompson
Main Conference Track
Chain of Thought Imitation with Procedure Cloning Mengjiao (Sherry) Yang, Dale Schuurmans, Pieter Abbeel, Ofir Nachum
Main Conference Track
Revisiting Optimal Convergence Rate for Smooth and Non-convex Stochastic Decentralized Optimization Kun Yuan, Xinmeng Huang, Yiming Chen, Xiaohan Zhang, Yingya Zhang, Pan Pan
Main Conference Track
Training with More Confidence: Mitigating Injected and Natural Backdoors During Training Zhenting Wang, Hailun Ding, Juan Zhai, Shiqing Ma
Main Conference Track
Out-of-Distribution Detection via Conditional Kernel Independence Model Yu Wang, Jingjing Zou, Jingyang Lin, Qing Ling, Yingwei Pan, Ting Yao, Tao Mei
Main Conference Track
Online Convex Optimization with Hard Constraints: Towards the Best of Two Worlds and Beyond Hengquan Guo, Xin Liu, Honghao Wei, Lei Ying
Main Conference Track
ResT V2: Simpler, Faster and Stronger Qinglong Zhang, Yu-Bin Yang
Main Conference Track
Object-Category Aware Reinforcement Learning Qi Yi, Rui Zhang, shaohui peng, Jiaming Guo, Xing Hu, Zidong Du, xishan zhang, Qi Guo, Yunji Chen
Main Conference Track
Learning Partial Equivariances From Data David W. Romero, Suhas Lohit
Main Conference Track
Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding Chitwan Saharia, William Chan, Saurabh Saxena, Lala Li, Jay Whang, Emily L Denton, Kamyar Ghasemipour, Raphael Gontijo Lopes, Burcu Karagol Ayan, Tim Salimans, Jonathan Ho, David J Fleet, Mohammad Norouzi
Main Conference Track
A Simple Decentralized Cross-Entropy Method Zichen Zhang, Jun Jin, Martin Jagersand, Jun Luo, Dale Schuurmans
Main Conference Track
MSDS: A Large-Scale Chinese Signature and Token Digit String Dataset for Handwriting Verification Peirong Zhang, Jiajia Jiang, Yuliang Liu, Lianwen Jin
Datasets and Benchmarks Track
Do Residual Neural Networks discretize Neural Ordinary Differential Equations? Michael Sander, Pierre Ablin, Gabriel Peyré
Main Conference Track
Diffusion-based Molecule Generation with Informative Prior Bridges Lemeng Wu, Chengyue Gong, Xingchao Liu, Mao Ye, Qiang Liu
Main Conference Track
Generative multitask learning mitigates target-causing confounding Taro Makino, Krzysztof Geras, Kyunghyun Cho
Main Conference Track
Revisit last-iterate convergence of mSGD under milder requirement on step size ruinan Jin, Xingkang He, Lang Chen, Difei Cheng, Vijay Gupta
Main Conference Track
Are You Stealing My Model? Sample Correlation for Fingerprinting Deep Neural Networks Jiyang Guan, Jian Liang, Ran He
Main Conference Track
SecureFedYJ: a safe feature Gaussianization protocol for Federated Learning Tanguy Marchand, Boris Muzellec, Constance Béguier, Jean Ogier du Terrail, Mathieu Andreux
Main Conference Track
When to Trust Your Simulator: Dynamics-Aware Hybrid Offline-and-Online Reinforcement Learning Haoyi Niu, shubham sharma, Yiwen Qiu, Ming Li, Guyue Zhou, Jianming HU, Xianyuan Zhan
Main Conference Track
Data-Efficient Structured Pruning via Submodular Optimization Marwa El Halabi, Suraj Srinivas, Simon Lacoste-Julien
Main Conference Track
Interpolation and Regularization for Causal Learning Leena Chennuru Vankadara, Luca Rendsburg, Ulrike V. Luxburg, Debarghya Ghoshdastidar
Main Conference Track
A Direct Approximation of AIXI Using Logical State Abstractions Samuel Yang-Zhao, Tianyu Wang, Kee Siong Ng
Main Conference Track
Learning Representations via a Robust Behavioral Metric for Deep Reinforcement Learning Jianda Chen, Sinno Pan
Main Conference Track
Finding Second-Order Stationary Points in Nonconvex-Strongly-Concave Minimax Optimization Luo Luo, Yujun Li, Cheng Chen
Main Conference Track
Contextual Squeeze-and-Excitation for Efficient Few-Shot Image Classification Massimiliano Patacchiola, John Bronskill, Aliaksandra Shysheya, Katja Hofmann, Sebastian Nowozin, Richard Turner
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Fuzzy Learning Machine Junbiao Cui, Jiye Liang
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Learning Structure from the Ground up---Hierarchical Representation Learning by Chunking Shuchen Wu, Noemi Elteto, Ishita Dasgupta, Eric Schulz
Main Conference Track
AMOS: A Large-Scale Abdominal Multi-Organ Benchmark for Versatile Medical Image Segmentation Yuanfeng Ji, Haotian Bai, Chongjian GE, Jie Yang, Ye Zhu, Ruimao Zhang, Zhen Li, Lingyan Zhanng, Wanling Ma, Xiang Wan, Ping Luo
Datasets and Benchmarks Track
The price of ignorance: how much does it cost to forget noise structure in low-rank matrix estimation? Jean Barbier, TianQi Hou, Marco Mondelli, Manuel Saenz
Main Conference Track
Scalable Interpretability via Polynomials Abhimanyu Dubey, Filip Radenovic, Dhruv Mahajan
Main Conference Track
DeVRF: Fast Deformable Voxel Radiance Fields for Dynamic Scenes Jia-Wei Liu, Yan-Pei Cao, Weijia Mao, Wenqiao Zhang, David Junhao Zhang, Jussi Keppo, Ying Shan, Xiaohu Qie, Mike Zheng Shou
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Hiding Images in Deep Probabilistic Models Haoyu Chen, Linqi Song, Zhenxing Qian, Xinpeng Zhang, Kede Ma
Main Conference Track
ViewFool: Evaluating the Robustness of Visual Recognition to Adversarial Viewpoints Yinpeng Dong, Shouwei Ruan, Hang Su, Caixin Kang, Xingxing Wei, Jun Zhu
Main Conference Track
Learning Superpoint Graph Cut for 3D Instance Segmentation Le Hui, Linghua Tang, Yaqi Shen, Jin Xie, Jian Yang
Main Conference Track
Estimating the Arc Length of the Optimal ROC Curve and Lower Bounding the Maximal AUC Song Liu
Main Conference Track
Acceleration in Distributed Sparse Regression Marie Maros, Gesualdo Scutari
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Latency-aware Spatial-wise Dynamic Networks Yizeng Han, Zhihang Yuan, Yifan Pu, Chenhao Xue, Shiji Song, Guangyu Sun, Gao Huang
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Towards Versatile Embodied Navigation Hanqing Wang, Wei Liang, Luc V Gool, Wenguan Wang
Main Conference Track
Explain My Surprise: Learning Efficient Long-Term Memory by predicting uncertain outcomes Artyom Sorokin, Nazar Buzun, Leonid Pugachev, Mikhail Burtsev
Main Conference Track
Polyhistor: Parameter-Efficient Multi-Task Adaptation for Dense Vision Tasks Yen-Cheng Liu, CHIH-YAO MA, Junjiao Tian, Zijian He, Zsolt Kira
Main Conference Track
LAPO: Latent-Variable Advantage-Weighted Policy Optimization for Offline Reinforcement Learning Xi Chen, Ali Ghadirzadeh, Tianhe Yu, Jianhao Wang, Alex Yuan Gao, Wenzhe Li, Liang Bin, Chelsea Finn, Chongjie Zhang
Main Conference Track
GAMA: Generative Adversarial Multi-Object Scene Attacks Abhishek Aich, Calvin-Khang Ta, Akash Gupta, Chengyu Song, Srikanth Krishnamurthy, Salman Asif, Amit Roy-Chowdhury
Main Conference Track
Predicting Label Distribution from Multi-label Ranking Yunan Lu, Xiuyi Jia
Main Conference Track
Trajectory of Mini-Batch Momentum: Batch Size Saturation and Convergence in High Dimensions Kiwon Lee, Andrew Cheng, Elliot Paquette, Courtney Paquette
Main Conference Track
Transformers from an Optimization Perspective Yongyi Yang, zengfeng Huang, David P Wipf
Main Conference Track
PDSketch: Integrated Domain Programming, Learning, and Planning Jiayuan Mao, Tomás Lozano-Pérez, Josh Tenenbaum, Leslie P. Kaelbling
Main Conference Track
Amortized Projection Optimization for Sliced Wasserstein Generative Models Khai Nguyen, Nhat Ho
Main Conference Track
GT-GAN: General Purpose Time Series Synthesis with Generative Adversarial Networks Jinsung Jeon, JEONGHAK KIM, Haryong Song, Seunghyeon Cho, Noseong Park
Main Conference Track
Heterogeneous Skill Learning for Multi-agent Tasks Yuntao Liu, Yuan Li, Xinhai Xu, Yong Dou, Donghong Liu
Main Conference Track
On Margin Maximization in Linear and ReLU Networks Gal Vardi, Ohad Shamir, Nati Srebro
Main Conference Track
Unsupervised Causal Generative Understanding of Images Titas Anciukevicius, Patrick Fox-Roberts, Edward Rosten, Paul Henderson
Main Conference Track
DART: Articulated Hand Model with Diverse Accessories and Rich Textures Daiheng Gao, Yuliang Xiu, Kailin Li, Lixin Yang, Feng Wang, Peng Zhang, Bang Zhang, Cewu Lu, Ping Tan
Datasets and Benchmarks Track
BadPrompt: Backdoor Attacks on Continuous Prompts Xiangrui Cai, Haidong Xu, Sihan Xu, Ying ZHANG, Yuan xiaojie
Main Conference Track
Off-Policy Evaluation with Policy-Dependent Optimization Response Wenshuo Guo, Michael I. Jordan, Angela Zhou
Main Conference Track
FIRE: Semantic Field of Words Represented as Non-Linear Functions Xin Du, Kumiko Tanaka-Ishii
Main Conference Track
Sampling in Constrained Domains with Orthogonal-Space Variational Gradient Descent Ruqi Zhang, Qiang Liu, Xin Tong
Main Conference Track
Change-point Detection for Sparse and Dense Functional Data in General Dimensions Carlos Misael Madrid Padilla, Daren Wang, Zifeng Zhao, Yi Yu
Main Conference Track
ClimbQ: Class Imbalanced Quantization Enabling Robustness on Efficient Inferences Ting-An Chen, De-Nian Yang, Ming-syan Chen
Main Conference Track
Look Around and Refer: 2D Synthetic Semantics Knowledge Distillation for 3D Visual Grounding Eslam Bakr, Yasmeen Alsaedy, Mohamed Elhoseiny
Main Conference Track
Nonstationary Dual Averaging and Online Fair Allocation Luofeng Liao, Yuan Gao, Christian Kroer
Main Conference Track
Incentivizing Combinatorial Bandit Exploration Xinyan Hu, Dung Ngo, Aleksandrs Slivkins, Steven Z. Wu
Main Conference Track
Transfer Learning on Heterogeneous Feature Spaces for Treatment Effects Estimation Ioana Bica, Mihaela van der Schaar
Main Conference Track
Is Out-of-Distribution Detection Learnable? Zhen Fang, Yixuan Li, Jie Lu, Jiahua Dong, Bo Han, Feng Liu
Main Conference Track
DMAP: a Distributed Morphological Attention Policy for learning to locomote with a changing body Alberto Silvio Chiappa, Alessandro Marin Vargas, Alexander Mathis
Main Conference Track
On the role of overparameterization in off-policy Temporal Difference learning with linear function approximation Valentin Thomas
Main Conference Track
Whitening Convergence Rate of Coupling-based Normalizing Flows Felix Draxler, Christoph Schnörr, Ullrich Köthe
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Neurosymbolic Deep Generative Models for Sequence Data with Relational Constraints Halley Young, Maxwell Du, Osbert Bastani
Main Conference Track
Semi-Supervised Generative Models for Multiagent Trajectories Dennis Fassmeyer, Pascal Fassmeyer, Ulf Brefeld
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PhysGNN: A Physics--Driven Graph Neural Network Based Model for Predicting Soft Tissue Deformation in Image--Guided Neurosurgery Yasmin Salehi, Dennis Giannacopoulos
Main Conference Track
Towards Diverse and Faithful One-shot Adaption of Generative Adversarial Networks Yabo Zhang, mingshuai Yao, Yuxiang Wei, Zhilong Ji, Jinfeng Bai, Wangmeng Zuo
Main Conference Track
Deep Bidirectional Language-Knowledge Graph Pretraining Michihiro Yasunaga, Antoine Bosselut, Hongyu Ren, Xikun Zhang, Christopher D Manning, Percy Liang, Jure Leskovec
Main Conference Track
Theoretical analysis of deep neural networks for temporally dependent observations Mingliang Ma, Abolfazl Safikhani
Main Conference Track
A Theoretical Framework for Inference Learning Nick Alonso, Beren Millidge, Jeffrey Krichmar, Emre O Neftci
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Cross-modal Learning for Image-Guided Point Cloud Shape Completion Emanuele Aiello, Diego Valsesia, Enrico Magli
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Coreset for Line-Sets Clustering Sagi Lotan, Ernesto Evgeniy Sanches Shayda, Dan Feldman
Main Conference Track
Robust On-Policy Sampling for Data-Efficient Policy Evaluation in Reinforcement Learning Rujie Zhong, Duohan Zhang, Lukas Schäfer, Stefano Albrecht, Josiah Hanna
Main Conference Track
Pre-Trained Model Reusability Evaluation for Small-Data Transfer Learning Yao-Xiang Ding, Xi-Zhu Wu, Kun Zhou, Zhi-Hua Zhou
Main Conference Track
Tree ensemble kernels for Bayesian optimization with known constraints over mixed-feature spaces Alexander Thebelt, Calvin Tsay, Robert Lee, Nathan Sudermann-Merx, David Walz, Behrang Shafei, Ruth Misener
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RLIP: Relational Language-Image Pre-training for Human-Object Interaction Detection Hangjie Yuan, Jianwen Jiang, Samuel Albanie, Tao Feng, Ziyuan Huang, Dong Ni, Mingqian Tang
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Skills Regularized Task Decomposition for Multi-task Offline Reinforcement Learning Minjong Yoo, SangWoo Cho, Honguk Woo
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Contextual Dynamic Pricing with Unknown Noise: Explore-then-UCB Strategy and Improved Regrets Yiyun Luo, Will Wei Sun, Yufeng Liu
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Adversarially Robust Learning: A Generic Minimax Optimal Learner and Characterization Omar Montasser, Steve Hanneke, Nati Srebro
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The Implicit Delta Method Nathan Kallus, James McInerney
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Singular Value Fine-tuning: Few-shot Segmentation requires Few-parameters Fine-tuning Yanpeng Sun, Qiang Chen, Xiangyu He, Jian Wang, Haocheng Feng, Junyu Han, Errui Ding, Jian Cheng, Zechao Li, Jingdong Wang
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On the relationship between variational inference and auto-associative memory Louis Annabi, Alexandre Pitti, Mathias Quoy
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Annihilation of Spurious Minima in Two-Layer ReLU Networks Yossi Arjevani, Michael Field
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A Closer Look at Weakly-Supervised Audio-Visual Source Localization Shentong Mo, Pedro Morgado
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Posterior Collapse of a Linear Latent Variable Model Zihao Wang, Liu Ziyin
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Accelerating SGD for Highly Ill-Conditioned Huge-Scale Online Matrix Completion Jialun Zhang, Hong-Ming Chiu, Richard Y Zhang
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Lifting Weak Supervision To Structured Prediction Harit Vishwakarma, Frederic Sala
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A Lagrangian Duality Approach to Active Learning Juan Elenter, Navid Naderializadeh, Alejandro Ribeiro
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Instance-optimal PAC Algorithms for Contextual Bandits Zhaoqi Li, Lillian Ratliff, houssam nassif, Kevin G. Jamieson, Lalit Jain
Main Conference Track
xView3-SAR: Detecting Dark Fishing Activity Using Synthetic Aperture Radar Imagery Fernando Paolo, Tsu-ting Tim Lin, Ritwik Gupta, Bryce Goodman, Nirav Patel, Daniel Kuster, David Kroodsma, Jared Dunnmon
Datasets and Benchmarks Track
Understanding the Failure of Batch Normalization for Transformers in NLP Jiaxi Wang, Ji Wu, Lei Huang
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Exploration via Elliptical Episodic Bonuses Mikael Henaff, Roberta Raileanu, Minqi Jiang, Tim Rocktäschel
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Efficient and Effective Multi-task Grouping via Meta Learning on Task Combinations Xiaozhuang Song, Shun Zheng, Wei Cao, James Yu, Jiang Bian
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Learning Fractional White Noises in Neural Stochastic Differential Equations Anh Tong, Thanh Nguyen-Tang, Toan Tran, Jaesik Choi
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CryptoGCN: Fast and Scalable Homomorphically Encrypted Graph Convolutional Network Inference Ran Ran, Wei Wang, Quan Gang, Jieming Yin, Nuo Xu, Wujie Wen
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UniGAN: Reducing Mode Collapse in GANs using a Uniform Generator Ziqi Pan, Li Niu, Liqing Zhang
Main Conference Track
UMIX: Improving Importance Weighting for Subpopulation Shift via Uncertainty-Aware Mixup Zongbo Han, Zhipeng Liang, Fan Yang, Liu Liu, Lanqing Li, Yatao Bian, Peilin Zhao, Bingzhe Wu, Changqing Zhang, Jianhua Yao
Main Conference Track
Exploit Reward Shifting in Value-Based Deep-RL: Optimistic Curiosity-Based Exploration and Conservative Exploitation via Linear Reward Shaping Hao Sun, Lei Han, Rui Yang, Xiaoteng Ma, Jian Guo, Bolei Zhou
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Stability and Generalization for Markov Chain Stochastic Gradient Methods Puyu Wang, Yunwen Lei, Yiming Ying, Ding-Xuan Zhou
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Degradation-Aware Unfolding Half-Shuffle Transformer for Spectral Compressive Imaging Yuanhao Cai, Jing Lin, Haoqian Wang, Xin Yuan, Henghui Ding, Yulun Zhang, Radu Timofte, Luc V Gool
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Deep Surrogate Assisted Generation of Environments Varun Bhatt, Bryon Tjanaka, Matthew Fontaine, Stefanos Nikolaidis
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Toward Equation of Motion for Deep Neural Networks: Continuous-time Gradient Descent and Discretization Error Analysis Taiki Miyagawa
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FLAIR: Federated Learning Annotated Image Repository Congzheng Song, Filip Granqvist, Kunal Talwar
Datasets and Benchmarks Track
Self-Supervised Pretraining for Large-Scale Point Clouds Zaiwei Zhang, Min Bai, Erran Li Li
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Vision Transformers provably learn spatial structure Samy Jelassi, Michael Sander, Yuanzhi Li
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Unsupervised Learning of Shape Programs with Repeatable Implicit Parts Boyang Deng, Sumith Kulal, Zhengyang Dong, Congyue Deng, Yonglong Tian, Jiajun Wu
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Detecting Abrupt Changes in Sequential Pairwise Comparison Data Wanshan Li, Alessandro Rinaldo, Daren Wang
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Rethinking Resolution in the Context of Efficient Video Recognition Chuofan Ma, Qiushan Guo, Yi Jiang, Ping Luo, Zehuan Yuan, Xiaojuan Qi
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The Effects of Regularization and Data Augmentation are Class Dependent Randall Balestriero, Leon Bottou, Yann LeCun
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Learning to Mitigate AI Collusion on Economic Platforms Gianluca Brero, Eric Mibuari, Nicolas Lepore, David C. Parkes
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The Query Complexity of Cake Cutting Simina Branzei, Noam Nisan
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PAC Prediction Sets for Meta-Learning Sangdon Park, Edgar Dobriban, Insup Lee, Osbert Bastani
Main Conference Track
High-dimensional Asymptotics of Feature Learning: How One Gradient Step Improves the Representation Jimmy Ba, Murat A Erdogdu, Taiji Suzuki, Zhichao Wang, Denny Wu, Greg Yang
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Pruning’s Effect on Generalization Through the Lens of Training and Regularization Tian Jin, Michael Carbin, Dan Roy, Jonathan Frankle, Gintare Karolina Dziugaite
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Cluster Randomized Designs for One-Sided Bipartite Experiments Jennifer Brennan, Vahab Mirrokni, Jean Pouget-Abadie
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Deep Equilibrium Approaches to Diffusion Models Ashwini Pokle, Zhengyang Geng, J. Zico Kolter
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Inducing Neural Collapse in Imbalanced Learning: Do We Really Need a Learnable Classifier at the End of Deep Neural Network? Yibo Yang, Shixiang Chen, Xiangtai Li, Liang Xie, Zhouchen Lin, Dacheng Tao
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Pruning Neural Networks via Coresets and Convex Geometry: Towards No Assumptions Murad Tukan, Loay Mualem, Alaa Maalouf
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Intermediate Prototype Mining Transformer for Few-Shot Semantic Segmentation YUANWEI LIU, Nian Liu, Xiwen Yao, Junwei Han
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Long-Form Video-Language Pre-Training with Multimodal Temporal Contrastive Learning Yuchong Sun, Hongwei Xue, Ruihua Song, Bei Liu, Huan Yang, Jianlong Fu
Main Conference Track
A new dataset for multilingual keyphrase generation Frédéric Piedboeuf, Philippe Langlais
Datasets and Benchmarks Track
Model Preserving Compression for Neural Networks Jerry Chee, Megan Flynn (née Renz), Anil Damle, Christopher M De Sa
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Neural Conservation Laws: A Divergence-Free Perspective Jack Richter-Powell, Yaron Lipman, Ricky T. Q. Chen
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Towards Effective Multi-Modal Interchanges in Zero-Resource Sounding Object Localization Yang Zhao, Chen Zhang, Haifeng Huang, Haoyuan Li, Zhou Zhao
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On the Convergence of Stochastic Multi-Objective Gradient Manipulation and Beyond Shiji Zhou, Wenpeng Zhang, Jiyan Jiang, Wenliang Zhong, Jinjie GU, Wenwu Zhu
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Decentralized Local Stochastic Extra-Gradient for Variational Inequalities Aleksandr Beznosikov, Pavel Dvurechenskii, Anastasiia Koloskova, Valentin Samokhin, Sebastian U Stich, Alexander Gasnikov
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Model Zoos: A Dataset of Diverse Populations of Neural Network Models Konstantin Schürholt, Diyar Taskiran, Boris Knyazev, Xavier Giró-i-Nieto, Damian Borth
Datasets and Benchmarks Track
Weakly-Supervised Multi-Granularity Map Learning for Vision-and-Language Navigation Peihao Chen, Dongyu Ji, Kunyang Lin, Runhao Zeng, Thomas Li, Mingkui Tan, Chuang Gan
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Thinned random measures for sparse graphs with overlapping communities Federica Zoe Ricci, Michele Guindani, Erik B. Sudderth
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Fine-tuning language models to find agreement among humans with diverse preferences Michiel Bakker, Martin Chadwick, Hannah Sheahan, Michael Tessler, Lucy Campbell-Gillingham, Jan Balaguer, Nat McAleese, Amelia Glaese, John Aslanides, Matt Botvinick, Christopher Summerfield
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What is a Good Metric to Study Generalization of Minimax Learners? Asuman Ozdaglar, Sarath Pattathil, Jiawei Zhang, Kaiqing Zhang
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Sequencer: Deep LSTM for Image Classification Yuki Tatsunami, Masato Taki
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Double Check Your State Before Trusting It: Confidence-Aware Bidirectional Offline Model-Based Imagination Jiafei Lyu, Xiu Li, Zongqing Lu
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Learning on Arbitrary Graph Topologies via Predictive Coding Tommaso Salvatori, Luca Pinchetti, Beren Millidge, Yuhang Song, Tianyi Bao, Rafal Bogacz, Thomas Lukasiewicz
Main Conference Track
Robustness Disparities in Face Detection Samuel Dooley, George Z Wei, Tom Goldstein, John Dickerson
Datasets and Benchmarks Track
Marksman Backdoor: Backdoor Attacks with Arbitrary Target Class Khoa D Doan, Yingjie Lao, Ping Li
Main Conference Track
Memorization Without Overfitting: Analyzing the Training Dynamics of Large Language Models Kushal Tirumala, Aram Markosyan, Luke Zettlemoyer, Armen Aghajanyan
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Bandit Theory and Thompson Sampling-Guided Directed Evolution for Sequence Optimization Hui Yuan, Chengzhuo Ni, Huazheng Wang, Xuezhou Zhang, Le Cong, Csaba Szepesvari, Mengdi Wang
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Scalable and Efficient Training of Large Convolutional Neural Networks with Differential Privacy Zhiqi Bu, Jialin Mao, Shiyun Xu
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Weakly supervised causal representation learning Johann Brehmer, Pim de Haan, Phillip Lippe, Taco S Cohen
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Zeroth-Order Negative Curvature Finding: Escaping Saddle Points without Gradients Hualin Zhang, Huan Xiong, Bin Gu
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Exposing and Exploiting Fine-Grained Block Structures for Fast and Accurate Sparse Training Peng Jiang, Lihan Hu, Shihui Song
Main Conference Track
DABS 2.0: Improved Datasets and Algorithms for Universal Self-Supervision Alex Tamkin, Gaurab Banerjee, Mohamed Owda, Vincent Liu, Shashank Rammoorthy, Noah Goodman
Datasets and Benchmarks Track
Operator Splitting Value Iteration Amin Rakhsha, Andrew Wang, Mohammad Ghavamzadeh, Amir-massoud Farahmand
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Enhanced Latent Space Blind Model for Real Image Denoising via Alternative Optimization Chao Ren, Yizhong Pan, Jie Huang
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Self-Explaining Deviations for Coordination Hengyuan Hu, Samuel Sokota, David Wu, Anton Bakhtin, Andrei Lupu, Brandon Cui, Jakob Foerster
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Communication Efficient Federated Learning for Generalized Linear Bandits Chuanhao Li, Hongning Wang
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Active Learning for Multiple Target Models Ying-Peng Tang, Sheng-Jun Huang
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Descent Steps of a Relation-Aware Energy Produce Heterogeneous Graph Neural Networks Hongjoon Ahn, Yongyi Yang, Quan Gan, Taesup Moon, David P Wipf
Main Conference Track
Multi-agent Performative Prediction with Greedy Deployment and Consensus Seeking Agents Qiang LI, Chung-Yiu Yau, Hoi-To Wai
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Preservation of the Global Knowledge by Not-True Distillation in Federated Learning Gihun Lee, Minchan Jeong, Yongjin Shin, Sangmin Bae, Se-Young Yun
Main Conference Track
Finite-Time Regret of Thompson Sampling Algorithms for Exponential Family Multi-Armed Bandits Tianyuan Jin, Pan Xu, Xiaokui Xiao, Anima Anandkumar
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Graph Reordering for Cache-Efficient Near Neighbor Search Benjamin Coleman, Santiago Segarra, Alexander J Smola, Anshumali Shrivastava
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MetaMask: Revisiting Dimensional Confounder for Self-Supervised Learning Jiangmeng Li, Wenwen Qiang, Yanan Zhang, Wenyi Mo, Changwen Zheng, Bing Su, Hui Xiong
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On Feature Learning in the Presence of Spurious Correlations Pavel Izmailov, Polina Kirichenko, Nate Gruver, Andrew G Wilson
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Sparse2Dense: Learning to Densify 3D Features for 3D Object Detection Tianyu Wang, Xiaowei Hu, Zhengzhe LIU, Chi-Wing Fu
Main Conference Track
Exploring Length Generalization in Large Language Models Cem Anil, Yuhuai Wu, Anders Andreassen, Aitor Lewkowycz, Vedant Misra, Vinay Ramasesh, Ambrose Slone, Guy Gur-Ari, Ethan Dyer, Behnam Neyshabur
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Stability and Generalization Analysis of Gradient Methods for Shallow Neural Networks Yunwen Lei, Rong Jin, Yiming Ying
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ViTPose: Simple Vision Transformer Baselines for Human Pose Estimation Yufei Xu, Jing Zhang, Qiming ZHANG, Dacheng Tao
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Re-Analyze Gauss: Bounds for Private Matrix Approximation via Dyson Brownian Motion Oren Mangoubi, Nisheeth Vishnoi
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ASPiRe: Adaptive Skill Priors for Reinforcement Learning Mengda Xu, Manuela M. Veloso, Shuran Song
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Neural Differential Equations for Learning to Program Neural Nets Through Continuous Learning Rules Kazuki Irie, Francesco Faccio, Jürgen Schmidhuber
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MEMO: Test Time Robustness via Adaptation and Augmentation Marvin Zhang, Sergey Levine, Chelsea Finn
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Learning-Augmented Algorithms for Online Linear and Semidefinite Programming Elena Grigorescu, Young-San Lin, Sandeep Silwal, Maoyuan Song, Samson Zhou
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Text-Adaptive Multiple Visual Prototype Matching for Video-Text Retrieval Chengzhi Lin, Ancong Wu, Junwei Liang, Jun Zhang, Wenhang Ge, Wei-Shi Zheng, Chunhua Shen
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Asymptotically Unbiased Instance-wise Regularized Partial AUC Optimization: Theory and Algorithm HuiYang Shao, Qianqian Xu, Zhiyong Yang, Shilong Bao, Qingming Huang
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Universality of Group Convolutional Neural Networks Based on Ridgelet Analysis on Groups Sho Sonoda, Isao Ishikawa, Masahiro Ikeda
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Error Correction Code Transformer Yoni Choukroun, Lior Wolf
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Towards Improving Calibration in Object Detection Under Domain Shift Muhammad Akhtar Munir, Muhammad Haris Khan, M. Sarfraz, Mohsen Ali
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Renyi Differential Privacy of Propose-Test-Release and Applications to Private and Robust Machine Learning Jiachen T. Wang, Saeed Mahloujifar, Shouda Wang, Ruoxi Jia, Prateek Mittal
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A Transformer-Based Object Detector with Coarse-Fine Crossing Representations Zhishan Li, Ying Nie, Kai Han, Jianyuan Guo, Lei Xie, Yunhe Wang
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Beyond Adult and COMPAS: Fair Multi-Class Prediction via Information Projection Wael Alghamdi, Hsiang Hsu, Haewon Jeong, Hao Wang, Peter Michalak, Shahab Asoodeh, Flavio Calmon
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Explicit Tradeoffs between Adversarial and Natural Distributional Robustness Mazda Moayeri, Kiarash Banihashem, Soheil Feizi
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Learning Latent Seasonal-Trend Representations for Time Series Forecasting Zhiyuan Wang, Xovee Xu, Weifeng Zhang, Goce Trajcevski, Ting Zhong, Fan Zhou
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JAHS-Bench-201: A Foundation For Research On Joint Architecture And Hyperparameter Search Archit Bansal, Danny Stoll, Maciej Janowski, Arber Zela, Frank Hutter
Datasets and Benchmarks Track
Capturing Graphs with Hypo-Elliptic Diffusions Csaba Toth, Darrick Lee, Celia Hacker, Harald Oberhauser
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A Spectral Approach to Item Response Theory Duc Nguyen, Anderson Ye Zhang
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FedSR: A Simple and Effective Domain Generalization Method for Federated Learning A. Tuan Nguyen, Philip Torr, Ser Nam Lim
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SIXO: Smoothing Inference with Twisted Objectives Dieterich Lawson, Allan Raventós, Andrew Warrington, Scott Linderman
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Explicable Policy Search Ze Gong, Yu ("Tony") Zhang
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Exploring evolution-aware & -free protein language models as protein function predictors Mingyang Hu, Fajie Yuan, Kevin Yang, Fusong Ju, Jin Su, Hui Wang, Fei Yang, Qiuyang Ding
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Breaking Bad: A Dataset for Geometric Fracture and Reassembly Silvia Sellán, Yun-Chun Chen, Ziyi Wu, Animesh Garg, Alec Jacobson
Datasets and Benchmarks Track
Fair and Optimal Decision Trees: A Dynamic Programming Approach Jacobus van der Linden, Mathijs de Weerdt, Emir Demirović
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Recommender Forest for Efficient Retrieval Chao Feng, Wuchao Li, Defu Lian, Zheng Liu, Enhong Chen
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Graph Few-shot Learning with Task-specific Structures Song Wang, Chen Chen, Jundong Li
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DASCO: Dual-Generator Adversarial Support Constrained Offline Reinforcement Learning Quan Vuong, Aviral Kumar, Sergey Levine, Yevgen Chebotar
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Beyond L1: Faster and Better Sparse Models with skglm Quentin Bertrand, Quentin Klopfenstein, Pierre-Antoine Bannier, Gauthier Gidel, Mathurin Massias
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You Can’t Count on Luck: Why Decision Transformers and RvS Fail in Stochastic Environments Keiran Paster, Sheila McIlraith, Jimmy Ba
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Cost-efficient Gaussian tensor network embeddings for tensor-structured inputs Linjian Ma, Edgar Solomonik
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Neural Transmitted Radiance Fields Chengxuan Zhu, Renjie Wan, Boxin Shi
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Geoclidean: Few-Shot Generalization in Euclidean Geometry Joy Hsu, Jiajun Wu, Noah Goodman
Datasets and Benchmarks Track
Enabling Detailed Action Recognition Evaluation Through Video Dataset Augmentation Jihoon Chung, Yu Wu, Olga Russakovsky
Datasets and Benchmarks Track
Unsupervised Skill Discovery via Recurrent Skill Training Zheyuan Jiang, Jingyue Gao, Jianyu Chen
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Structural Kernel Search via Bayesian Optimization and Symbolical Optimal Transport Matthias Bitzer, Mona Meister, Christoph Zimmer
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Robust Models are less Over-Confident Julia Grabinski, Paul Gavrikov, Janis Keuper, Margret Keuper
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Near-Optimal No-Regret Learning Dynamics for General Convex Games Gabriele Farina, Ioannis Anagnostides, Haipeng Luo, Chung-Wei Lee, Christian Kroer, Tuomas Sandholm
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OTKGE: Multi-modal Knowledge Graph Embeddings via Optimal Transport Zongsheng Cao, Qianqian Xu, Zhiyong Yang, Yuan He, Xiaochun Cao, Qingming Huang
Main Conference Track
ComMU: Dataset for Combinatorial Music Generation Hyun Lee, Taehyun Kim, Hyolim Kang, Minjoo Ki, Hyeonchan Hwang, kwanho park, Sharang Han, Seon Joo Kim
Datasets and Benchmarks Track

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