Advances in Neural Information Processing Systems 17

NIPS 2004

Edited by L. Saul and Y. Weiss and L. Bottou

207 papers

PAC-Bayes Learning of Conjunctions and Classification of Gene-Expression Data Mario Marchand, Mohak Shah
A Second Order Cone programming Formulation for Classifying Missing Data Chiranjib Bhattacharyya, Pannagadatta K. Shivaswamy, Alex J. Smola
Learning first-order Markov models for control Pieter Abbeel, Andrew Y. Ng
Who's In the Picture Tamara L. Berg, Alexander C. Berg, Jaety Edwards, David A. Forsyth
Optimal Aggregation of Classifiers and Boosting Maps in Functional Magnetic Resonance Imaging Vladimir Koltchinskii, Manel Martínez-ramón, Stefan Posse
Binet-Cauchy Kernels Alex J. Smola, S.v.n. Vishwanathan
Synergistic Face Detection and Pose Estimation with Energy-Based Models Margarita Osadchy, Matthew L. Miller, Yann L. Cun
The power of feature clustering: An application to object detection Shai Avidan, Moshe Butman
Synergies between Intrinsic and Synaptic Plasticity in Individual Model Neurons Jochen Triesch
A Probabilistic Model for Online Document Clustering with Application to Novelty Detection Jian Zhang, Zoubin Ghahramani, Yiming Yang
Non-Local Manifold Tangent Learning Yoshua Bengio, Martin Monperrus
Maximal Margin Labeling for Multi-Topic Text Categorization Hideto Kazawa, Tomonori Izumitani, Hirotoshi Taira, Eisaku Maeda
Conditional Random Fields for Object Recognition Ariadna Quattoni, Michael Collins, Trevor Darrell
Inference, Attention, and Decision in a Bayesian Neural Architecture Angela J. Yu, Peter Dayan
Exponential Family Harmoniums with an Application to Information Retrieval Max Welling, Michal Rosen-zvi, Geoffrey E. Hinton
Distributed Occlusion Reasoning for Tracking with Nonparametric Belief Propagation Erik B. Sudderth, Michael I. Mandel, William T. Freeman, Alan S. Willsky
An Investigation of Practical Approximate Nearest Neighbor Algorithms Ting Liu, Andrew W. Moore, Ke Yang, Alexander G. Gray
Hierarchical Distributed Representations for Statistical Language Modeling John Blitzer, Fernando Pereira, Kilian Q. Weinberger, Lawrence K. Saul
Discrete profile alignment via constrained information bottleneck Sean O'rourke, Gal Chechik, Robin Friedman, Eleazar Eskin
Multiple Relational Embedding Roland Memisevic, Geoffrey E. Hinton
Conditional Models of Identity Uncertainty with Application to Noun Coreference Andrew McCallum, Ben Wellner
Outlier Detection with One-class Kernel Fisher Discriminants Volker Roth
Kernel Projection Machine: a New Tool for Pattern Recognition Laurent Zwald, Gilles Blanchard, Pascal Massart, Régis Vert
Seeing through water Alexei Efros, Volkan Isler, Jianbo Shi, Mirkó Visontai
Generative Affine Localisation and Tracking John Winn, Andrew Blake
Schema Learning: Experience-Based Construction of Predictive Action Models Michael P. Holmes, Charles Jr.
Machine Learning Applied to Perception: Decision Images for Gender Classification Felix A. Wichmann, Arnulf B. Graf, Heinrich H. Bülthoff, Eero P. Simoncelli, Bernhard Schölkopf
An Information Maximization Model of Eye Movements Laura W. Renninger, James M. Coughlan, Preeti Verghese, Jitendra Malik
Learning Hyper-Features for Visual Identification Andras D. Ferencz, Erik G. Learned-miller, Jitendra Malik
Parametric Embedding for Class Visualization Tomoharu Iwata, Kazumi Saito, Naonori Ueda, Sean Stromsten, Thomas L. Griffiths, Joshua B. Tenenbaum
A Topographic Support Vector Machine: Classification Using Local Label Configurations Johannes Mohr, Klaus Obermayer
New Criteria and a New Algorithm for Learning in Multi-Agent Systems Rob Powers, Yoav Shoham
The Cerebellum Chip: an Analog VLSI Implementation of a Cerebellar Model of Classical Conditioning Constanze Hofstoetter, Manuel Gil, Kynan Eng, Giacomo Indiveri, Matti Mintz, Jörg Kramer, Paul F. Verschure
Pictorial Structures for Molecular Modeling: Interpreting Density Maps Frank Dimaio, George Phillips, Jude W. Shavlik
Support Vector Classification with Input Data Uncertainty Jinbo Bi, Tong Zhang
Planning for Markov Decision Processes with Sparse Stochasticity Maxim Likhachev, Sebastian Thrun, Geoffrey J. Gordon
Expectation Consistent Free Energies for Approximate Inference Manfred Opper, Ole Winther
Using Machine Learning to Break Visual Human Interaction Proofs (HIPs) Kumar Chellapilla, Patrice Y. Simard
Making Latin Manuscripts Searchable using gHMM's Jaety Edwards, Yee W. Teh, Roger Bock, Michael Maire, Grace Vesom, David A. Forsyth
Nonparametric Transforms of Graph Kernels for Semi-Supervised Learning Xiaojin Zhu, Jaz Kandola, Zoubin Ghahramani, John D. Lafferty
Sparse Coding of Natural Images Using an Overcomplete Set of Limited Capacity Units Eizaburo Doi, Michael S. Lewicki
Optimal Information Decoding from Neuronal Populations with Specific Stimulus Selectivity Marcelo A. Montemurro, Stefano Panzeri
Implicit Wiener Series for Higher-Order Image Analysis Matthias O. Franz, Bernhard Schölkopf
Following Curved Regularized Optimization Solution Paths Saharon Rosset
Learning, Regularization and Ill-Posed Inverse Problems Lorenzo Rosasco, Andrea Caponnetto, Ernesto D. Vito, Francesca Odone, Umberto D. Giovannini
Density Level Detection is Classification Ingo Steinwart, Don Hush, Clint Scovel
Learning Syntactic Patterns for Automatic Hypernym Discovery Rion Snow, Daniel Jurafsky, Andrew Y. Ng
Joint Tracking of Pose, Expression, and Texture using Conditionally Gaussian Filters Tim K. Marks, J. C. Roddey, Javier R. Movellan, John R. Hershey
Multiple Alignment of Continuous Time Series Jennifer Listgarten, Radford M. Neal, Sam T. Roweis, Andrew Emili
Hierarchical Clustering of a Mixture Model Jacob Goldberger, Sam T. Roweis
Hierarchical Bayesian Inference in Networks of Spiking Neurons Rajesh P. Rao
Efficient Kernel Discriminant Analysis via QR Decomposition Tao Xiong, Jieping Ye, Qi Li, Ravi Janardan, Vladimir Cherkassky
Semi-parametric Exponential Family PCA Sajama Sajama, Alon Orlitsky
Self-Tuning Spectral Clustering Lihi Zelnik-manor, Pietro Perona
The Entire Regularization Path for the Support Vector Machine Saharon Rosset, Robert Tibshirani, Ji Zhu, Trevor J. Hastie
The Laplacian PDF Distance: A Cost Function for Clustering in a Kernel Feature Space Robert Jenssen, Deniz Erdogmus, Jose Principe, Torbjørn Eltoft
Experts in a Markov Decision Process Eyal Even-dar, Sham M. Kakade, Yishay Mansour
Neighbourhood Components Analysis Jacob Goldberger, Geoffrey E. Hinton, Sam T. Roweis, Ruslan Salakhutdinov
Learning Gaussian Process Kernels via Hierarchical Bayes Anton Schwaighofer, Volker Tresp, Kai Yu
Nonlinear Blind Source Separation by Integrating Independent Component Analysis and Slow Feature Analysis Tobias Blaschke, Laurenz Wiskott
Solitaire: Man Versus Machine Xiang Yan, Persi Diaconis, Paat Rusmevichientong, Benjamin V. Roy
A Machine Learning Approach to Conjoint Analysis Olivier Chapelle, Zaïd Harchaoui
Intrinsically Motivated Reinforcement Learning Nuttapong Chentanez, Andrew G. Barto, Satinder P. Singh
Joint Probabilistic Curve Clustering and Alignment Scott J. Gaffney, Padhraic Smyth
Triangle Fixing Algorithms for the Metric Nearness Problem Suvrit Sra, Joel Tropp, Inderjit S. Dhillon
Economic Properties of Social Networks Sham M. Kakade, Michael Kearns, Luis E. Ortiz, Robin Pemantle, Siddharth Suri
Beat Tracking the Graphical Model Way Dustin Lang, Nando D. Freitas
Large-Scale Prediction of Disulphide Bond Connectivity Jianlin Cheng, Alessandro Vullo, Pierre F. Baldi
An Application of Boosting to Graph Classification Taku Kudo, Eisaku Maeda, Yuji Matsumoto
Multi-agent Cooperation in Diverse Population Games K. Wong, S. W. Lim, Z. Gao
Modeling Nonlinear Dependencies in Natural Images using Mixture of Laplacian Distribution Hyun J. Park, Te W. Lee
Dependent Gaussian Processes Phillip Boyle, Marcus Frean
Synchronization of neural networks by mutual learning and its application to cryptography Einat Klein, Rachel Mislovaty, Ido Kanter, Andreas Ruttor, Wolfgang Kinzel
Semigroup Kernels on Finite Sets Marco Cuturi, Jean-philippe Vert
A Hidden Markov Model for de Novo Peptide Sequencing Bernd Fischer, Volker Roth, Jonas Grossmann, Sacha Baginsky, Wilhelm Gruissem, Franz Roos, Peter Widmayer, Joachim M. Buhmann
Instance-Based Relevance Feedback for Image Retrieval Giorgio Gia\-cin\-to, Fabio Roli
Learning Preferences for Multiclass Problems Fabio Aiolli, Alessandro Sperduti
Mass Meta-analysis in Talairach Space Finn \. Nielsen
Result Analysis of the NIPS 2003 Feature Selection Challenge Isabelle Guyon, Steve Gunn, Asa Ben-Hur, Gideon Dror
Sub-Microwatt Analog VLSI Support Vector Machine for Pattern Classification and Sequence Estimation Shantanu Chakrabartty, Gert Cauwenberghs
Maximum Margin Clustering Linli Xu, James Neufeld, Bryce Larson, Dale Schuurmans
On the Adaptive Properties of Decision Trees Clayton Scott, Robert Nowak
Kernel Methods for Implicit Surface Modeling Joachim Giesen, Simon Spalinger, Bernhard Schölkopf
Neural Network Computation by In Vitro Transcriptional Circuits Jongmin Kim, John Hopfield, Erik Winfree
Similarity and Discrimination in Classical Conditioning: A Latent Variable Account Aaron C. Courville, Nathaniel D. Daw, David S. Touretzky
Boosting on Manifolds: Adaptive Regularization of Base Classifiers Ligen Wang, Balázs Kégl
Surface Reconstruction using Learned Shape Models Jan E. Solem, Fredrik Kahl
Reducing Spike Train Variability: A Computational Theory Of Spike-Timing Dependent Plasticity Sander M. Bohte, Michael Mozer
Maximum Likelihood Estimation of Intrinsic Dimension Elizaveta Levina, Peter J. Bickel
Distributed Information Regularization on Graphs Adrian Corduneanu, Tommi S. Jaakkola
The Convergence of Contrastive Divergences Alan L. Yuille
Log-concavity Results on Gaussian Process Methods for Supervised and Unsupervised Learning Liam Paninski
Incremental Algorithms for Hierarchical Classification Nicolò Cesa-bianchi, Claudio Gentile, Andrea Tironi, Luca Zaniboni
On Semi-Supervised Classification Balaji Krishnapuram, David Williams, Ya Xue, Lawrence Carin, Mário Figueiredo, Alexander J. Hartemink
Joint MRI Bias Removal Using Entropy Minimization Across Images Erik G. Learned-miller, Parvez Ahammad
Chemosensory Processing in a Spiking Model of the Olfactory Bulb: Chemotopic Convergence and Center Surround Inhibition Baranidharan Raman, Ricardo Gutierrez-osuna
Using Random Forests in the Structured Language Model Peng Xu, Frederick Jelinek
Exploration-Exploitation Tradeoffs for Experts Algorithms in Reactive Environments Daniela D. Farias, Nimrod Megiddo
Unsupervised Variational Bayesian Learning of Nonlinear Models Antti Honkela, Harri Valpola
VDCBPI: an Approximate Scalable Algorithm for Large POMDPs Pascal Poupart, Craig Boutilier
A Generalized Bradley-Terry Model: From Group Competition to Individual Skill Tzu-kuo Huang, Chih-jen Lin, Ruby C. Weng
Rate- and Phase-coded Autoassociative Memory Máté Lengyel, Peter Dayan
Constraining a Bayesian Model of Human Visual Speed Perception Alan Stocker, Eero P. Simoncelli
Efficient Kernel Machines Using the Improved Fast Gauss Transform Changjiang Yang, Ramani Duraiswami, Larry S. Davis
Responding to Modalities with Different Latencies Fredrik Bissmarck, Hiroyuki Nakahara, Kenji Doya, Okihide Hikosaka
Two-Dimensional Linear Discriminant Analysis Jieping Ye, Ravi Janardan, Qi Li
Assignment of Multiplicative Mixtures in Natural Images Odelia Schwartz, Terrence J. Sejnowski, Peter Dayan
Convergence and No-Regret in Multiagent Learning Michael Bowling
Learning Efficient Auditory Codes Using Spikes Predicts Cochlear Filters Evan C. Smith, Michael S. Lewicki
Active Learning for Anomaly and Rare-Category Detection Dan Pelleg, Andrew W. Moore
A Feature Selection Algorithm Based on the Global Minimization of a Generalization Error Bound Dori Peleg, Ron Meir
Semi-supervised Learning with Penalized Probabilistic Clustering Zhengdong Lu, Todd K. Leen
A Direct Formulation for Sparse PCA Using Semidefinite Programming Alexandre D'aspremont, Laurent E. Ghaoui, Michael I. Jordan, Gert R. Lanckriet
Stable adaptive control with online learning H. J. Kim, Andrew Y. Ng
The Rescorla-Wagner Algorithm and Maximum Likelihood Estimation of Causal Parameters Alan L. Yuille
Contextual Models for Object Detection Using Boosted Random Fields Antonio Torralba, Kevin P. Murphy, William T. Freeman
An Auditory Paradigm for Brain-Computer Interfaces N. J. Hill, Thomas N. Lal, Karin Bierig, Niels Birbaumer, Bernhard Schölkopf
Worst-Case Analysis of Selective Sampling for Linear-Threshold Algorithms Nicolò Cesa-bianchi, Claudio Gentile, Luca Zaniboni
Markov Networks for Detecting Overalpping Elements in Sequence Data Mark Craven, Joseph Bockhorst
Co-Validation: Using Model Disagreement on Unlabeled Data to Validate Classification Algorithms Omid Madani, David M. Pennock, Gary W. Flake
Co-Training and Expansion: Towards Bridging Theory and Practice Maria-florina Balcan, Avrim Blum, Ke Yang
Probabilistic Inference of Alternative Splicing Events in Microarray Data Ofer Shai, Brendan J. Frey, Quaid D. Morris, Qun Pan, Christine Misquitta, Benjamin J. Blencowe
Semi-supervised Learning by Entropy Minimization Yves Grandvalet, Yoshua Bengio
Detecting Significant Multidimensional Spatial Clusters Daniel B. Neill, Andrew W. Moore, Francisco Pereira, Tom M. Mitchell
Message Errors in Belief Propagation Alexander T. Ihler, John W. Fisher, Alan S. Willsky
Methods Towards Invasive Human Brain Computer Interfaces Thomas N. Lal, Thilo Hinterberger, Guido Widman, Michael Schröder, N. J. Hill, Wolfgang Rosenstiel, Christian E. Elger, Niels Birbaumer, Bernhard Schölkopf
A Three Tiered Approach for Articulated Object Action Modeling and Recognition Le Lu, Gregory D. Hager, Laurent Younes
Temporal-Difference Networks Richard S. Sutton, Brian Tanner
Methods for Estimating the Computational Power and Generalization Capability of Neural Microcircuits Wolfgang Maass, Robert A. Legenstein, Nils Bertschinger
The Variational Ising Classifier (VIC) Algorithm for Coherently Contaminated Data Oliver Williams, Andrew Blake, Roberto Cipolla
Generalization Error and Algorithmic Convergence of Median Boosting Balázs Kégl
Supervised Graph Inference Jean-philippe Vert, Yoshihiro Yamanishi
Confidence Intervals for the Area Under the ROC Curve Corinna Cortes, Mehryar Mohri
Maximising Sensitivity in a Spiking Network Anthony J. Bell, Lucas C. Parra
Probabilistic Computation in Spiking Populations Richard S. Zemel, Rama Natarajan, Peter Dayan, Quentin J. Huys
Theory of localized synfire chain: characteristic propagation speed of stable spike pattern Kosuke Hamaguchi, Masato Okada, Kazuyuki Aihara
Semi-supervised Learning on Directed Graphs Dengyong Zhou, Thomas Hofmann, Bernhard Schölkopf
Class-size Independent Generalization Analsysis of Some Discriminative Multi-Category Classification Tong Zhang
ℓ₀-norm Minimization for Basis Selection David P. Wipf, Bhaskar D. Rao
The Power of Selective Memory: Self-Bounded Learning of Prediction Suffix Trees Ofer Dekel, Shai Shalev-shwartz, Yoram Singer
Modelling Uncertainty in the Game of Go David H. Stern, Thore Graepel, David MacKay
Spike Sorting: Bayesian Clustering of Non-Stationary Data Aharon Bar-hillel, Adam Spiro, Eran Stark
Harmonising Chorales by Probabilistic Inference Moray Allan, Christopher Williams
Nearly Tight Bounds for the Continuum-Armed Bandit Problem Robert D. Kleinberg
Mistake Bounds for Maximum Entropy Discrimination Philip M. Long, Xinyu Wu
A Harmonic Excitation State-Space Approach to Blind Separation of Speech Rasmus K. Olsson, Lars K. Hansen
Matrix Exponential Gradient Updates for On-line Learning and Bregman Projection Koji Tsuda, Gunnar Rätsch, Manfred K. Warmuth
Blind One-microphone Speech Separation: A Spectral Learning Approach Francis R. Bach, Michael I. Jordan
Resolving Perceptual Aliasing In The Presence Of Noisy Sensors Guy Shani, Ronen I. Brafman
Kernels for Multi--task Learning Charles A. Micchelli, Massimiliano Pontil
Variational Minimax Estimation of Discrete Distributions under KL Loss Liam Paninski
Online Bounds for Bayesian Algorithms Sham M. Kakade, Andrew Y. Ng
Analysis of a greedy active learning strategy Sanjoy Dasgupta
A Cost-Shaping LP for Bellman Error Minimization with Performance Guarantees Daniela D. Farias, Benjamin V. Roy
Validity Estimates for Loopy Belief Propagation on Binary Real-world Networks Joris M. Mooij, Hilbert J. Kappen
Bayesian inference in spiking neurons Sophie Deneve
Computing regularization paths for learning multiple kernels Francis R. Bach, Romain Thibaux, Michael I. Jordan
Saliency-Driven Image Acuity Modulation on a Reconfigurable Array of Spiking Silicon Neurons R. J. Vogelstein, Udayan Mallik, Eugenio Culurciello, Gert Cauwenberghs, Ralph Etienne-Cummings
Common-Frame Model for Object Recognition Pierre Moreels, Pietro Perona
Brain Inspired Reinforcement Learning Françcois Rivest, Yoshua Bengio, John Kalaska
Semi-supervised Learning via Gaussian Processes Neil D. Lawrence, Michael I. Jordan
Parallel Support Vector Machines: The Cascade SVM Hans P. Graf, Eric Cosatto, Léon Bottou, Igor Dourdanovic, Vladimir Vapnik
Sampling Methods for Unsupervised Learning Rob Fergus, Andrew Zisserman, Pietro Perona
Limits of Spectral Clustering Ulrike V. Luxburg, Olivier Bousquet, Mikhail Belkin
Using the Equivalent Kernel to Understand Gaussian Process Regression Peter Sollich, Christopher Williams
Newscast EM Wojtek Kowalczyk, Nikos Vlassis
Dynamic Bayesian Networks for Brain-Computer Interfaces Pradeep Shenoy, Rajesh P. Rao
Edge of Chaos Computation in Mixed-Mode VLSI - A Hard Liquid Felix Schürmann, Karlheinz Meier, Johannes Schemmel
Breaking SVM Complexity with Cross-Training Léon Bottou, Jason Weston, Gökhan H. Bakir
Linear Multilayer Independent Component Analysis for Large Natural Scenes Yoshitatsu Matsuda, Kazunori Yamaguchi
Identifying Protein-Protein Interaction Sites on a Genome-Wide Scale Haidong Wang, Eran Segal, Asa Ben-Hur, Daphne Koller, Douglas L. Brutlag
Proximity Graphs for Clustering and Manifold Learning Richard S. Zemel, Miguel Á. Carreira-Perpiñán
Fast Rates to Bayes for Kernel Machines Ingo Steinwart, Clint Scovel
Discriminant Saliency for Visual Recognition from Cluttered Scenes Dashan Gao, Nuno Vasconcelos
Bayesian Regularization and Nonnegative Deconvolution for Time Delay Estimation Yuanqing Lin, Daniel D. Lee
Algebraic Set Kernels with Application to Inference Over Local Image Representations Amnon Shashua, Tamir Hazan
The Correlated Correspondence Algorithm for Unsupervised Registration of Nonrigid Surfaces Dragomir Anguelov, Praveen Srinivasan, Hoi-cheung Pang, Daphne Koller, Sebastian Thrun, James Davis
Maximum-Margin Matrix Factorization Nathan Srebro, Jason Rennie, Tommi S. Jaakkola
Real-Time Pitch Determination of One or More Voices by Nonnegative Matrix Factorization Fei Sha, Lawrence K. Saul
Efficient Out-of-Sample Extension of Dominant-Set Clusters Massimiliano Pavan, Marcello Pelillo
Instance-Specific Bayesian Model Averaging for Classification Shyam Visweswaran, Gregory F. Cooper
Hierarchical Eigensolver for Transition Matrices in Spectral Methods Chakra Chennubhotla, Allan D. Jepson
Exponentiated Gradient Algorithms for Large-margin Structured Classification Peter L. Bartlett, Michael Collins, Ben Taskar, David A. McAllester
A Method for Inferring Label Sampling Mechanisms in Semi-Supervised Learning Saharon Rosset, Ji Zhu, Hui Zou, Trevor J. Hastie
Semi-Markov Conditional Random Fields for Information Extraction Sunita Sarawagi, William W. Cohen
Adaptive Manifold Learning Jing Wang, Zhenyue Zhang, Hongyuan Zha
Euclidean Embedding of Co-Occurrence Data Amir Globerson, Gal Chechik, Fernando Pereira, Naftali Tishby
Heuristics for Ordering Cue Search in Decision Making Peter M. Todd, Anja Dieckmann
Coarticulation in Markov Decision Processes Khashayar Rohanimanesh, Robert Platt, Sridhar Mahadevan, Roderic Grupen
Integrating Topics and Syntax Thomas L. Griffiths, Mark Steyvers, David M. Blei, Joshua B. Tenenbaum
Object Classification from a Single Example Utilizing Class Relevance Metrics Michael Fink
A Large Deviation Bound for the Area Under the ROC Curve Shivani Agarwal, Thore Graepel, Ralf Herbrich, Dan Roth
Adaptive Discriminative Generative Model and Its Applications Ruei-sung Lin, David A. Ross, Jongwoo Lim, Ming-Hsuan Yang
Optimal sub-graphical models Mukund Narasimhan, Jeff A. Bilmes
Modeling Conversational Dynamics as a Mixed-Memory Markov Process Tanzeem Choudhury, Sumit Basu
Generalization Error Bounds for Collaborative Prediction with Low-Rank Matrices Nathan Srebro, Noga Alon, Tommi S. Jaakkola
Incremental Learning for Visual Tracking Jongwoo Lim, David A. Ross, Ruei-sung Lin, Ming-Hsuan Yang
Face Detection --- Efficient and Rank Deficient Wolf Kienzle, Matthias O. Franz, Bernhard Schölkopf, Gökhan H. Bakir
A Temporal Kernel-Based Model for Tracking Hand Movements from Neural Activities Lavi Shpigelman, Koby Crammer, Rony Paz, Eilon Vaadia, Yoram Singer
On-Chip Compensation of Device-Mismatch Effects in Analog VLSI Neural Networks Miguel Figueroa, Seth Bridges, Chris Diorio
At the Edge of Chaos: Real-time Computations and Self-Organized Criticality in Recurrent Neural Networks Nils Bertschinger, Thomas Natschläger, Robert A. Legenstein
Trait Selection for Assessing Beef Meat Quality Using Non-linear SVM Juan Coz, Gustavo F. Bayón, Jorge Díez, Oscar Luaces, Antonio Bahamonde, Carlos Sañudo
Sharing Clusters among Related Groups: Hierarchical Dirichlet Processes Yee W. Teh, Michael I. Jordan, Matthew J. Beal, David M. Blei
Spike-timing Dependent Plasticity and Mutual Information Maximization for a Spiking Neuron Model Taro Toyoizumi, Jean-pascal Pfister, Kazuyuki Aihara, Wulfram Gerstner
Approximately Efficient Online Mechanism Design David C. Parkes, Dimah Yanovsky, Satinder P. Singh
Comparing Beliefs, Surveys, and Random Walks Erik Aurell, Uri Gordon, Scott Kirkpatrick
Theories of Access Consciousness Michael D. Colagrosso, Michael Mozer

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