Advances in Neural Information Processing Systems 19

NIPS 2006

Edited by B. Schölkopf and J. Platt and T. Hoffman

ISBN: 9781622760381

204 papers

Ordinal Regression by Extended Binary Classification Ling Li, Hsuan-tien Lin
Learning to Traverse Image Manifolds Piotr Dollár, Vincent Rabaud, Serge J. Belongie
Game Theoretic Algorithms for Protein-DNA binding Luis Pérez-breva, Luis E. Ortiz, Chen-hsiang Yeang, Tommi S. Jaakkola
Kernel Maximum Entropy Data Transformation and an Enhanced Spectral Clustering Algorithm Robert Jenssen, Torbjørn Eltoft, Mark Girolami, Deniz Erdogmus
Unified Inference for Variational Bayesian Linear Gaussian State-Space Models David Barber, Silvia Chiappa
Graph Laplacian Regularization for Large-Scale Semidefinite Programming Kilian Q. Weinberger, Fei Sha, Qihui Zhu, Lawrence K. Saul
Multi-Task Feature Learning Andreas Argyriou, Theodoros Evgeniou, Massimiliano Pontil
Predicting spike times from subthreshold dynamics of a neuron Ryota Kobayashi, Shigeru Shinomoto
Blind source separation for over-determined delayed mixtures Lars Omlor, Martin Giese
Multiple timescales and uncertainty in motor adaptation Konrad P. Körding, Joshua B. Tenenbaum, Reza Shadmehr
Learning from Multiple Sources Koby Crammer, Michael Kearns, Jennifer Wortman
Modeling Human Motion Using Binary Latent Variables Graham W. Taylor, Geoffrey E. Hinton, Sam T. Roweis
Bayesian Image Super-resolution, Continued Lyndsey C. Pickup, David P. Capel, Stephen J. Roberts, Andrew Zisserman
Geometric entropy minimization (GEM) for anomaly detection and localization Alfred O. Hero
Bayesian Ensemble Learning Hugh A. Chipman, Edward I. George, Robert E. Mcculloch
The Robustness-Performance Tradeoff in Markov Decision Processes Huan Xu, Shie Mannor
Combining causal and similarity-based reasoning Charles Kemp, Patrick Shafto, Allison Berke, Joshua B. Tenenbaum
Detecting Humans via Their Pose Alessandro Bissacco, Ming-Hsuan Yang, Stefano Soatto
Hidden Markov Dirichlet Process: Modeling Genetic Recombination in Open Ancestral Space Kyung-ah Sohn, Eric P. Xing
Online Classification for Complex Problems Using Simultaneous Projections Yonatan Amit, Shai Shalev-shwartz, Yoram Singer
Convex Repeated Games and Fenchel Duality Shai Shalev-shwartz, Yoram Singer
Towards a general independent subspace analysis Fabian J. Theis
In-Network PCA and Anomaly Detection Ling Huang, Xuanlong Nguyen, Minos Garofalakis, Michael I. Jordan, Anthony Joseph, Nina Taft
Robotic Grasping of Novel Objects Ashutosh Saxena, Justin Driemeyer, Justin Kearns, Andrew Y. Ng
Bayesian Detection of Infrequent Differences in Sets of Time Series with Shared Structure Jennifer Listgarten, Radford M. Neal, Sam T. Roweis, Rachel Puckrin, Sean Cutler
Training Conditional Random Fields for Maximum Labelwise Accuracy Samuel S. Gross, Olga Russakovsky, Chuong B. Do, Serafim Batzoglou
Modeling Dyadic Data with Binary Latent Factors Edward Meeds, Zoubin Ghahramani, Radford M. Neal, Sam T. Roweis
Reducing Calibration Time For Brain-Computer Interfaces: A Clustering Approach Matthias Krauledat, Michael Schröder, Benjamin Blankertz, Klaus-Robert Müller
Theory and Dynamics of Perceptual Bistability Paul R. Schrater, Rashmi Sundareswara
Aggregating Classification Accuracy across Time: Application to Single Trial EEG Steven Lemm, Christin Schäfer, Gabriel Curio
Blind Motion Deblurring Using Image Statistics Anat Levin
Accelerated Variational Dirichlet Process Mixtures Kenichi Kurihara, Max Welling, Nikos Vlassis
Online Clustering of Moving Hyperplanes René Vidal
Efficient sparse coding algorithms Honglak Lee, Alexis Battle, Rajat Raina, Andrew Y. Ng
Approximate Correspondences in High Dimensions Kristen Grauman, Trevor Darrell
Temporal Coding using the Response Properties of Spiking Neurons Thomas Voegtlin
A Nonparametric Bayesian Method for Inferring Features From Similarity Judgments Daniel J. Navarro, Thomas L. Griffiths
Hierarchical Dirichlet Processes with Random Effects Seyoung Kim, Padhraic Smyth
Bayesian Model Scoring in Markov Random Fields Sridevi Parise, Max Welling
Isotonic Conditional Random Fields and Local Sentiment Flow Yi Mao, Guy Lebanon
Logistic Regression for Single Trial EEG Classification Ryota Tomioka, Kazuyuki Aihara, Klaus-Robert Müller
A Local Learning Approach for Clustering Mingrui Wu, Bernhard Schölkopf
Temporal and Cross-Subject Probabilistic Models for fMRI Prediction Tasks Alexis Battle, Gal Chechik, Daphne Koller
Particle Filtering for Nonparametric Bayesian Matrix Factorization Frank Wood, Thomas L. Griffiths
Large-Scale Sparsified Manifold Regularization Ivor W. Tsang, James T. Kwok
Non-rigid point set registration: Coherent Point Drift Andriy Myronenko, Xubo Song, Miguel Á. Carreira-Perpiñán
Learning Nonparametric Models for Probabilistic Imitation David B. Grimes, Daniel R. Rashid, Rajesh P. Rao
Active learning for misspecified generalized linear models Francis R. Bach
Tighter PAC-Bayes Bounds Amiran Ambroladze, Emilio Parrado-hernández, John S. Shawe-taylor
Statistical Modeling of Images with Fields of Gaussian Scale Mixtures Siwei Lyu, Eero P. Simoncelli
Near-Uniform Sampling of Combinatorial Spaces Using XOR Constraints Carla P. Gomes, Ashish Sabharwal, Bart Selman
Recursive Attribute Factoring David Cohn, Deepak Verma, Karl Pfleger
Information Bottleneck for Non Co-Occurrence Data Yevgeny Seldin, Noam Slonim, Naftali Tishby
A Probabilistic Algorithm Integrating Source Localization and Noise Suppression of MEG and EEG data Johanna M. Zumer, Hagai T. Attias, Kensuke Sekihara, Srikantan S. Nagarajan
Attentional Processing on a Spike-Based VLSI Neural Network Yingxue Wang, Rodney J. Douglas, Shih-Chii Liu
A Bayesian Approach to Diffusion Models of Decision-Making and Response Time Michael D. Lee, Ian G. Fuss, Daniel J. Navarro
Graph-Based Visual Saliency Jonathan Harel, Christof Koch, Pietro Perona
Doubly Stochastic Normalization for Spectral Clustering Ron Zass, Amnon Shashua
A Scalable Machine Learning Approach to Go Lin Wu, Pierre F. Baldi
Stratification Learning: Detecting Mixed Density and Dimensionality in High Dimensional Point Clouds Gloria Haro, Gregory Randall, Guillermo Sapiro
A Collapsed Variational Bayesian Inference Algorithm for Latent Dirichlet Allocation Yee W. Teh, David Newman, Max Welling
Dynamic Foreground/Background Extraction from Images and Videos using Random Patches Le Lu, Gregory D. Hager
Subordinate class recognition using relational object models Aharon B. Hillel, Daphna Weinshall
Dirichlet-Enhanced Spam Filtering based on Biased Samples Steffen Bickel, Tobias Scheffer
Stability of $K$-Means Clustering Alexander Rakhlin, Andrea Caponnetto
Convergence of Laplacian Eigenmaps Mikhail Belkin, Partha Niyogi
Bayesian Policy Gradient Algorithms Mohammad Ghavamzadeh, Yaakov Engel
Handling Advertisements of Unknown Quality in Search Advertising Sandeep Pandey, Christopher Olston
Part-based Probabilistic Point Matching using Equivalence Constraints Graham Mcneill, Sethu Vijayakumar
Greedy Layer-Wise Training of Deep Networks Yoshua Bengio, Pascal Lamblin, Dan Popovici, Hugo Larochelle
Optimal Change-Detection and Spiking Neurons Angela J. Yu
Temporal dynamics of information content carried by neurons in the primary visual cortex Danko Nikolić, Stefan Haeusler, Wolf Singer, Wolfgang Maass
A Switched Gaussian Process for Estimating Disparity and Segmentation in Binocular Stereo Oliver Williams
Automated Hierarchy Discovery for Planning in Partially Observable Environments Laurent Charlin, Pascal Poupart, Romy Shioda
Adaptor Grammars: A Framework for Specifying Compositional Nonparametric Bayesian Models Mark Johnson, Thomas L. Griffiths, Sharon Goldwater
On Transductive Regression Corinna Cortes, Mehryar Mohri
Large Margin Multi-channel Analog-to-Digital Conversion with Applications to Neural Prosthesis Amit Gore, Shantanu Chakrabartty
Comparative Gene Prediction using Conditional Random Fields Jade P. Vinson, David Decaprio, Matthew D. Pearson, Stacey Luoma, James E. Galagan
Learning annotated hierarchies from relational data Daniel M. Roy, Charles Kemp, Vikash K. Mansinghka, Joshua B. Tenenbaum
Single Channel Speech Separation Using Factorial Dynamics John R. Hershey, Trausti Kristjansson, Steven Rennie, Peder A. Olsen
A Small World Threshold for Economic Network Formation Eyal Even-dar, Michael Kearns
iLSTD: Eligibility Traces and Convergence Analysis Alborz Geramifard, Michael Bowling, Martin Zinkevich, Richard S. Sutton
Sparse Kernel Orthonormalized PLS for feature extraction in large data sets Jerónimo Arenas-garcía, Kaare B. Petersen, Lars K. Hansen
Data Integration for Classification Problems Employing Gaussian Process Priors Mark Girolami, Mingjun Zhong
Stochastic Relational Models for Discriminative Link Prediction Kai Yu, Wei Chu, Shipeng Yu, Volker Tresp, Zhao Xu
Adaptive Spatial Filters with predefined Region of Interest for EEG based Brain-Computer-Interfaces Moritz Grosse-wentrup, Klaus Gramann, Martin Buss
A recipe for optimizing a time-histogram Hideaki Shimazaki, Shigeru Shinomoto
Inducing Metric Violations in Human Similarity Judgements Julian Laub, Klaus-Robert Müller, Felix A. Wichmann, Jakob H. Macke
Nonnegative Sparse PCA Ron Zass, Amnon Shashua
Context dependent amplification of both rate and event-correlation in a VLSI network of spiking neurons Elisabetta Chicca, Giacomo Indiveri, Rodney J. Douglas
PAC-Bayes Bounds for the Risk of the Majority Vote and the Variance of the Gibbs Classifier Alexandre Lacasse, François Laviolette, Mario Marchand, Pascal Germain, Nicolas Usunier
Generalized Regularized Least-Squares Learning with Predefined Features in a Hilbert Space Wenye Li, Kin-hong Lee, Kwong-sak Leung
Map-Reduce for Machine Learning on Multicore Cheng-tao Chu, Sang K. Kim, Yi-an Lin, Yuanyuan Yu, Gary Bradski, Kunle Olukotun, Andrew Y. Ng
Natural Actor-Critic for Road Traffic Optimisation Silvia Richter, Douglas Aberdeen, Jin Yu
Implicit Surfaces with Globally Regularised and Compactly Supported Basis Functions Christian Walder, Olivier Chapelle, Bernhard Schölkopf
Multiple Instance Learning for Computer Aided Diagnosis Murat Dundar, Balaji Krishnapuram, R. B. Rao, Glenn M. Fung
A selective attention multi--chip system with dynamic synapses and spiking neurons Chiara Bartolozzi, Giacomo Indiveri
Real-time adaptive information-theoretic optimization of neurophysiology experiments Jeremy Lewi, Robert Butera, Liam Paninski
High-Dimensional Graphical Model Selection Using $\ell_1$-Regularized Logistic Regression Martin J. Wainwright, John D. Lafferty, Pradeep K. Ravikumar
Efficient Learning of Sparse Representations with an Energy-Based Model Marc'aurelio Ranzato, Christopher Poultney, Sumit Chopra, Yann L. Cun
Learning Time-Intensity Profiles of Human Activity using Non-Parametric Bayesian Models Alexander T. Ihler, Padhraic Smyth
Using Combinatorial Optimization within Max-Product Belief Propagation Daniel Tarlow, Gal Elidan, Daphne Koller, John C. Duchi
Branch and Bound for Semi-Supervised Support Vector Machines Olivier Chapelle, Vikas Sindhwani, S. S. Keerthi
Differential Entropic Clustering of Multivariate Gaussians Jason V. Davis, Inderjit S. Dhillon
Multi-Instance Multi-Label Learning with Application to Scene Classification Zhi-Li Zhang, Min-ling Zhang
Analysis of Contour Motions Ce Liu, William T. Freeman, Edward H. Adelson
Learning to be Bayesian without Supervision Martin Raphan, Eero P. Simoncelli
Causal inference in sensorimotor integration Konrad P. Körding, Joshua B. Tenenbaum
A Kernel Subspace Method by Stochastic Realization for Learning Nonlinear Dynamical Systems Yoshinobu Kawahara, Takehisa Yairi, Kazuo Machida
Approximate inference using planar graph decomposition Amir Globerson, Tommi S. Jaakkola
Context Effects in Category Learning: An Investigation of Four Probabilistic Models Michael Mozer, Michael Shettel, Michael P. Holmes
An Application of Reinforcement Learning to Aerobatic Helicopter Flight Pieter Abbeel, Adam Coates, Morgan Quigley, Andrew Y. Ng
Parameter Expanded Variational Bayesian Methods Tommi S. Jaakkola, Yuan Qi
An EM Algorithm for Localizing Multiple Sound Sources in Reverberant Environments Michael I. Mandel, Daniel P. Ellis, Tony Jebara
Recursive ICA Honghao Shan, Lingyun Zhang, Garrison W. Cottrell
The Neurodynamics of Belief Propagation on Binary Markov Random Fields Thomas Ott, Ruedi Stoop
Unsupervised Learning of a Probabilistic Grammar for Object Detection and Parsing Yuanhao Chen, Long Zhu, Alan L. Yuille
A Humanlike Predictor of Facial Attractiveness Amit Kagian, Gideon Dror, Tommer Leyvand, Daniel Cohen-or, Eytan Ruppin
Mutagenetic tree Fisher kernel improves prediction of HIV drug resistance from viral genotype Tobias Sing, Niko Beerenwinkel
Image Retrieval and Classification Using Local Distance Functions Andrea Frome, Yoram Singer, Jitendra Malik
Chained Boosting Christian R. Shelton, Wesley Huie, Kin F. Kan
Support Vector Machines on a Budget Ofer Dekel, Yoram Singer
Manifold Denoising Matthias Hein, Markus Maier
Learning to Model Spatial Dependency: Semi-Supervised Discriminative Random Fields Chi-hoon Lee, Shaojun Wang, Feng Jiao, Dale Schuurmans, Russell Greiner
Shifting, One-Inclusion Mistake Bounds and Tight Multiclass Expected Risk Bounds Benjamin I. Rubinstein, Peter L. Bartlett, J. H. Rubinstein
Learning to parse images of articulated bodies Deva Ramanan
Correcting Sample Selection Bias by Unlabeled Data Jiayuan Huang, Arthur Gretton, Karsten Borgwardt, Bernhard Schölkopf, Alex J. Smola
A Nonparametric Approach to Bottom-Up Visual Saliency Wolf Kienzle, Felix A. Wichmann, Matthias O. Franz, Bernhard Schölkopf
Computation of Similarity Measures for Sequential Data using Generalized Suffix Trees Konrad Rieck, Pavel Laskov, Sören Sonnenburg
Randomized PCA Algorithms with Regret Bounds that are Logarithmic in the Dimension Manfred K. Warmuth, Dima Kuzmin
Efficient Structure Learning of Markov Networks using $L_1$-Regularization Su-in Lee, Varun Ganapathi, Daphne Koller
Attribute-efficient learning of decision lists and linear threshold functions under unconcentrated distributions Philip M. Long, Rocco Servedio
Mixture Regression for Covariate Shift Masashi Sugiyama, Amos J. Storkey
implicit Online Learning with Kernels Li Cheng, Dale Schuurmans, Shaojun Wang, Terry Caelli, S.v.n. Vishwanathan
PG-means: learning the number of clusters in data Yu Feng, Greg Hamerly
Conditional Random Sampling: A Sketch-based Sampling Technique for Sparse Data Ping Li, Kenneth W. Church, Trevor J. Hastie
Multi-Robot Negotiation: Approximating the Set of Subgame Perfect Equilibria in General-Sum Stochastic Games Chris Murray, Geoffrey J. Gordon
Optimal Single-Class Classification Strategies Ran El-Yaniv, Mordechai Nisenson
Learning to Rank with Nonsmooth Cost Functions Christopher J. Burges, Robert Ragno, Quoc V. Le
Analysis of Representations for Domain Adaptation Shai Ben-David, John Blitzer, Koby Crammer, Fernando Pereira
Neurophysiological Evidence of Cooperative Mechanisms for Stereo Computation Jason M. Samonds, Brian R. Potetz, Tai S. Lee
Sparse Multinomial Logistic Regression via Bayesian L1 Regularisation Gavin C. Cawley, Nicola L. Talbot, Mark Girolami
Gaussian and Wishart Hyperkernels Risi Kondor, Tony Jebara
A Complexity-Distortion Approach to Joint Pattern Alignment Andrea Vedaldi, Stefano Soatto
AdaBoost is Consistent Peter L. Bartlett, Mikhail Traskin
Cross-Validation Optimization for Large Scale Hierarchical Classification Kernel Methods Matthias Seeger
Effects of Stress and Genotype on Meta-parameter Dynamics in Reinforcement Learning Gediminas Lukšys, Jérémie Knüsel, Denis Sheynikhovich, Carmen Sandi, Wulfram Gerstner
A Novel Gaussian Sum Smoother for Approximate Inference in Switching Linear Dynamical Systems David Barber, Bertrand Mesot
Information Bottleneck Optimization and Independent Component Extraction with Spiking Neurons Stefan Klampfl, Wolfgang Maass, Robert A. Legenstein
A Theory of Retinal Population Coding Eizaburo Doi, Michael S. Lewicki
An Approach to Bounded Rationality Eli Ben-sasson, Ehud Kalai, Adam Kalai
Fundamental Limitations of Spectral Clustering Boaz Nadler, Meirav Galun
Generalized Maximum Margin Clustering and Unsupervised Kernel Learning Hamed Valizadegan, Rong Jin
Clustering Under Prior Knowledge with Application to Image Segmentation Dong S. Cheng, Vittorio Murino, Mário Figueiredo
Inferring Network Structure from Co-Occurrences Michael G. Rabbat, Mário Figueiredo, Robert Nowak
Logarithmic Online Regret Bounds for Undiscounted Reinforcement Learning Peter Auer, Ronald Ortner
Fast Iterative Kernel PCA Nicol N. Schraudolph, Simon Günter, S.v.n. Vishwanathan
Uncertainty, phase and oscillatory hippocampal recall Máté Lengyel, Peter Dayan
Speakers optimize information density through syntactic reduction T. F. Jaeger, Roger P. Levy
Learning Structural Equation Models for fMRI Enrico Simonotto, Heather Whalley, Stephen Lawrie, Lawrence Murray, David Mcgonigle, Amos J. Storkey
Simplifying Mixture Models through Function Approximation Kai Zhang, James T. Kwok
Sparse Representation for Signal Classification Ke Huang, Selin Aviyente
Similarity by Composition Oren Boiman, Michal Irani
An Information Theoretic Framework for Eukaryotic Gradient Sensing Joseph M. Kimmel, Richard M. Salter, Peter J. Thomas
Prediction on a Graph with a Perceptron Mark Herbster, Massimiliano Pontil
An Efficient Method for Gradient-Based Adaptation of Hyperparameters in SVM Models S. S. Keerthi, Vikas Sindhwani, Olivier Chapelle
Analysis of Empirical Bayesian Methods for Neuroelectromagnetic Source Localization Rey Ramírez, Jason Palmer, Scott Makeig, Bhaskar D. Rao, David P. Wipf
Efficient Methods for Privacy Preserving Face Detection Shai Avidan, Moshe Butman
Balanced Graph Matching Timothee Cour, Praveen Srinivasan, Jianbo Shi
Fast Discriminative Visual Codebooks using Randomized Clustering Forests Frank Moosmann, Bill Triggs, Frederic Jurie
Learning Motion Style Synthesis from Perceptual Observations Lorenzo Torresani, Peggy Hackney, Christoph Bregler
Linearly-solvable Markov decision problems Emanuel Todorov
Learning on Graph with Laplacian Regularization Rie K. Ando, Tong Zhang
An Oracle Inequality for Clipped Regularized Risk Minimizers Ingo Steinwart, Don Hush, Clint Scovel
Clustering appearance and shape by learning jigsaws Anitha Kannan, John Winn, Carsten Rother
Large Margin Component Analysis Lorenzo Torresani, Kuang-chih Lee
Kernels on Structured Objects Through Nested Histograms Marco Cuturi, Kenji Fukumizu
Learning with Hypergraphs: Clustering, Classification, and Embedding Dengyong Zhou, Jiayuan Huang, Bernhard Schölkopf
Learning Dense 3D Correspondence Florian Steinke, Volker Blanz, Bernhard Schölkopf
Fast Computation of Graph Kernels Karsten Borgwardt, Nicol N. Schraudolph, S.v.n. Vishwanathan
Multi-dynamic Bayesian Networks Karim Filali, Jeff A. Bilmes
Max-margin classification of incomplete data Gal Chechik, Geremy Heitz, Gal Elidan, Pieter Abbeel, Daphne Koller
Scalable Discriminative Learning for Natural Language Parsing and Translation Joseph Turian, Benjamin Wellington, I. D. Melamed
On the Relation Between Low Density Separation, Spectral Clustering and Graph Cuts Hariharan Narayanan, Mikhail Belkin, Partha Niyogi
A Kernel Method for the Two-Sample-Problem Arthur Gretton, Karsten Borgwardt, Malte Rasch, Bernhard Schölkopf, Alex J. Smola
Modeling General and Specific Aspects of Documents with a Probabilistic Topic Model Chaitanya Chemudugunta, Padhraic Smyth, Mark Steyvers
Emergence of conjunctive visual features by quadratic independent component analysis J.t. Lindgren, Aapo Hyvärinen
Nonlinear physically-based models for decoding motor-cortical population activity Gregory Shakhnarovich, Sung-phil Kim, Michael J. Black
Conditional mean field Peter Carbonetto, Nando D. Freitas
Unsupervised Regression with Applications to Nonlinear System Identification Ali Rahimi, Ben Recht
Large Margin Hidden Markov Models for Automatic Speech Recognition Fei Sha, Lawrence K. Saul
No-regret Algorithms for Online Convex Programs Geoffrey J. Gordon
A PAC-Bayes Risk Bound for General Loss Functions Pascal Germain, Alexandre Lacasse, François Laviolette, Mario Marchand
Distributed Inference in Dynamical Systems Stanislav Funiak, Carlos Guestrin, Rahul Sukthankar, Mark A. Paskin
Modelling transcriptional regulation using Gaussian Processes Neil D. Lawrence, Guido Sanguinetti, Magnus Rattray
TrueSkill™: A Bayesian Skill Rating System Ralf Herbrich, Tom Minka, Thore Graepel
Learnability and the doubling dimension Yi Li, Philip M. Long
Sample Complexity of Policy Search with Known Dynamics Peter L. Bartlett, Ambuj Tewari
Large Scale Hidden Semi-Markov SVMs Gunnar Rätsch, Sören Sonnenburg
MLLE: Modified Locally Linear Embedding Using Multiple Weights Zhenyue Zhang, Jing Wang
Hyperparameter Learning for Graph Based Semi-supervised Learning Algorithms Xinhua Zhang, Wee S. Lee
Boosting Structured Prediction for Imitation Learning J. A. Bagnell, Joel Chestnutt, David M. Bradley, Nathan D. Ratliff
Denoising and Dimension Reduction in Feature Space Mikio L. Braun, Klaus-Robert Müller, Joachim M. Buhmann
Relational Learning with Gaussian Processes Wei Chu, Vikas Sindhwani, Zoubin Ghahramani, S. S. Keerthi

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