Book

Reinforcement Learning with Function Approximation Converges to a Region Geoffrey J. Gordon

Redundancy and Dimensionality Reduction in Sparse-Distributed Representations of Natural Objects in Terms of Their Local Features Penio S. Penev

Who Does What? A Novel Algorithm to Determine Function Localization Ranit Aharonov-Barki, Isaac Meilijson, Eytan Ruppin

Overfitting in Neural Nets: Backpropagation, Conjugate Gradient, and Early Stopping Rich Caruana, Steve Lawrence, C. Lee Giles

Color Opponency Constitutes a Sparse Representation for the Chromatic Structure of Natural Scenes Te-Won Lee, Thomas Wachtler, Terrence J. Sejnowski

Learning Segmentation by Random Walks Marina Meila, Jianbo Shi

A PAC-Bayesian Margin Bound for Linear Classifiers: Why SVMs work Ralf Herbrich, Thore Graepel

Active Learning for Parameter Estimation in Bayesian Networks Simon Tong, Daphne Koller

A Tighter Bound for Graphical Models Martijn A. R. Leisink, Hilbert J. Kappen

Occam's Razor Carl Edward Rasmussen, Zoubin Ghahramani

Exact Solutions to Time-Dependent MDPs Justin A. Boyan, Michael L. Littman

An Information Maximization Approach to Overcomplete and Recurrent Representations Oren Shriki, Haim Sompolinsky, Daniel D. Lee

A Linear Programming Approach to Novelty Detection Colin Campbell, Kristin P. Bennett

Programmable Reinforcement Learning Agents David Andre, Stuart J. Russell

Learning Joint Statistical Models for Audio-Visual Fusion and Segregation John W. Fisher III, Trevor Darrell, William T. Freeman, Paul A. Viola

Convergence of Large Margin Separable Linear Classification Tong Zhang

Emergence of Movement Sensitive Neurons' Properties by Learning a Sparse Code for Natural Moving Images Rafal Bogacz, Malcolm W. Brown, Christophe G. Giraud-Carrier

High-temperature Expansions for Learning Models of Nonnegative Data Oliver B. Downs

A Support Vector Method for Clustering Asa Ben-Hur, David Horn, Hava T. Siegelmann, Vladimir Vapnik

Incremental and Decremental Support Vector Machine Learning Gert Cauwenberghs, Tomaso Poggio

Active Inference in Concept Learning Jonathan D. Nelson, Javier R. Movellan

The Interplay of Symbolic and Subsymbolic Processes in Anagram Problem Solving David B. Grimes, Michael Mozer

Using the Nyström Method to Speed Up Kernel Machines Christopher K. I. Williams, Matthias Seeger

Sex with Support Vector Machines Baback Moghaddam, Ming-Hsuan Yang

Recognizing Hand-written Digits Using Hierarchical Products of Experts Guy Mayraz, Geoffrey E. Hinton

APRICODD: Approximate Policy Construction Using Decision Diagrams Robert St-Aubin, Jesse Hoey, Craig Boutilier

Four-legged Walking Gait Control Using a Neuromorphic Chip Interfaced to a Support Vector Learning Algorithm Susanne Still, Bernhard Schölkopf, Klaus Hepp, Rodney J. Douglas

A Mathematical Programming Approach to the Kernel Fisher Algorithm Sebastian Mika, Gunnar Rätsch, Klaus-Robert Müller

Using Free Energies to Represent Q-values in a Multiagent Reinforcement Learning Task Brian Sallans, Geoffrey E. Hinton

Dopamine Bonuses Sham Kakade, Peter Dayan

Sparse Greedy Gaussian Process Regression Alex J. Smola, Peter L. Bartlett

Large Scale Bayes Point Machines Ralf Herbrich, Thore Graepel

Efficient Learning of Linear Perceptrons Shai Ben-David, Hans-Ulrich Simon

Gaussianization Scott Saobing Chen, Ramesh A. Gopinath

Error-correcting Codes on a Bethe-like Lattice Renato Vicente, David Saad, Yoshiyuki Kabashima

Homeostasis in a Silicon Integrate and Fire Neuron Shih-Chii Liu, Bradley A. Minch

Incorporating Second-Order Functional Knowledge for Better Option Pricing Charles Dugas, Yoshua Bengio, François Bélisle, Claude Nadeau, René Garcia

Spike-Timing-Dependent Learning for Oscillatory Networks Silvia Scarpetta, Zhaoping Li, John A. Hertz

On Reversing Jensen's Inequality Tony Jebara, Alex Pentland

From Mixtures of Mixtures to Adaptive Transform Coding Cynthia Archer, Todd K. Leen

Algorithmic Stability and Generalization Performance Olivier Bousquet, André Elisseeff

The Kernel Trick for Distances Bernhard Schölkopf

Higher-Order Statistical Properties Arising from the Non-Stationarity of Natural Signals Lucas C. Parra, Clay Spence, Paul Sajda

Probabilistic Semantic Video Indexing Milind R. Naphade, Igor Kozintsev, Thomas S. Huang

Accumulator Networks: Suitors of Local Probability Propagation Brendan J. Frey, Anitha Kannan

Sparse Representation for Gaussian Process Models Lehel Csató, Manfred Opper

Hippocampally-Dependent Consolidation in a Hierarchical Model of Neocortex Szabolcs Káli, Peter Dayan

Automated State Abstraction for Options using the U-Tree Algorithm Anders Jonsson, Andrew G. Barto

Structure Learning in Human Causal Induction Joshua B. Tenenbaum, Thomas L. Griffiths

Minimum Bayes Error Feature Selection for Continuous Speech Recognition George Saon, Mukund Padmanabhan

Bayesian Video Shot Segmentation Nuno Vasconcelos, Andrew Lippman

Kernel Expansions with Unlabeled Examples Martin Szummer, Tommi Jaakkola

Universality and Individuality in a Neural Code Elad Schneidman, Naama Brenner, Naftali Tishby, Robert R. de Ruyter van Steveninck, William Bialek

Generalized Belief Propagation Jonathan S. Yedidia, William T. Freeman, Yair Weiss

Multiple Timescales of Adaptation in a Neural Code Adrienne L. Fairhall, Geoffrey D. Lewen, William Bialek, Robert R. de Ruyter van Steveninck

Speech Denoising and Dereverberation Using Probabilistic Models Hagai Attias, John C. Platt, Alex Acero, Li Deng

Modelling Spatial Recall, Mental Imagery and Neglect Suzanna Becker, Neil Burgess

Adaptive Object Representation with Hierarchically-Distributed Memory Sites Bosco S. Tjan

Text Classification using String Kernels Huma Lodhi, John Shawe-Taylor, Nello Cristianini, Christopher J. C. H. Watkins

Model Complexity, Goodness of Fit and Diminishing Returns Igor V. Cadez, Padhraic Smyth

Fast Training of Support Vector Classifiers Fernando Pérez-Cruz, Pedro Luis Alarcón-Diana, Angel Navia-Vázquez, Antonio Artés-Rodríguez

Some New Bounds on the Generalization Error of Combined Classifiers Vladimir Koltchinskii, Dmitriy Panchenko, Fernando Lozano

Beyond Maximum Likelihood and Density Estimation: A Sample-Based Criterion for Unsupervised Learning of Complex Models Sepp Hochreiter, Michael Mozer

A Neural Probabilistic Language Model Yoshua Bengio, Réjean Ducharme, Pascal Vincent

Support Vector Novelty Detection Applied to Jet Engine Vibration Spectra Paul M. Hayton, Bernhard Schölkopf, Lionel Tarassenko, Paul Anuzis

`N-Body' Problems in Statistical Learning Alexander G. Gray, Andrew W. Moore

A Silicon Primitive for Competitive Learning David Hsu, Miguel Figueroa, Chris Diorio

Automatic Choice of Dimensionality for PCA Thomas P. Minka

Propagation Algorithms for Variational Bayesian Learning Zoubin Ghahramani, Matthew J. Beal

An Adaptive Metric Machine for Pattern Classification Carlotta Domeniconi, Jing Peng, Dimitrios Gunopulos

On Iterative Krylov-Dogleg Trust-Region Steps for Solving Neural Networks Nonlinear Least Squares Problems Eiji Mizutani, James Demmel

Stability and Noise in Biochemical Switches William Bialek

Computing with Finite and Infinite Networks Ole Winther

Hierarchical Memory-Based Reinforcement Learning Natalia Hernandez-Gardiol, Sridhar Mahadevan

Second Order Approximations for Probability Models Hilbert J. Kappen, Wim Wiegerinck

Feature Selection for SVMs Jason Weston, Sayan Mukherjee, Olivier Chapelle, Massimiliano Pontil, Tomaso Poggio, Vladimir Vapnik

Direct Classification with Indirect Data Timothy X. Brown

Constrained Independent Component Analysis Wei Lu, Jagath C. Rajapakse

A Gradient-Based Boosting Algorithm for Regression Problems Richard S. Zemel, Toniann Pitassi

The Early Word Catches the Weights Mark A. Smith, Garrison W. Cottrell, Karen L. Anderson

The Manhattan World Assumption: Regularities in Scene Statistics which Enable Bayesian Inference James M. Coughlan, Alan L. Yuille

Processing of Time Series by Neural Circuits with Biologically Realistic Synaptic Dynamics Thomas Natschläger, Wolfgang Maass, Eduardo D. Sontag, Anthony M. Zador

Machine Learning for Video-Based Rendering Arno Schödl, Irfan A. Essa

Discovering Hidden Variables: A Structure-Based Approach Gal Elidan, Noam Lotner, Nir Friedman, Daphne Koller

Natural Sound Statistics and Divisive Normalization in the Auditory System Odelia Schwartz, Eero P. Simoncelli

Regularized Winnow Methods Tong Zhang

FaceSync: A Linear Operator for Measuring Synchronization of Video Facial Images and Audio Tracks Malcolm Slaney, Michele Covell

Mixtures of Gaussian Processes Volker Tresp

What Can a Single Neuron Compute? Blaise Agüera y Arcas, Adrienne L. Fairhall, William Bialek

Tree-Based Modeling and Estimation of Gaussian Processes on Graphs with Cycles Martin J. Wainwright, Erik B. Sudderth, Alan S. Willsky

Learning Winner-take-all Competition Between Groups of Neurons in Lateral Inhibitory Networks Xiaohui Xie, Richard H. R. Hahnloser, H. Sebastian Seung

Foundations for a Circuit Complexity Theory of Sensory Processing Robert A. Legenstein, Wolfgang Maass

Bayes Networks on Ice: Robotic Search for Antarctic Meteorites Liam Pedersen, Dimitrios Apostolopoulos, William Whittaker

Learning and Tracking Cyclic Human Motion Dirk Ormoneit, Hedvig Sidenbladh, Michael J. Black, Trevor Hastie

The Use of MDL to Select among Computational Models of Cognition In Jae Myung, Mark A. Pitt, Shaobo Zhang, Vijay Balasubramanian

Active Support Vector Machine Classification Olvi L. Mangasarian, David R. Musicant

Decomposition of Reinforcement Learning for Admission Control of Self-Similar Call Arrival Processes Jakob Carlström

Generalizable Singular Value Decomposition for Ill-posed Datasets Ulrik Kjems, Lars Kai Hansen, Stephen C. Strother

Vicinal Risk Minimization Olivier Chapelle, Jason Weston, Léon Bottou, Vladimir Vapnik

Sparse Kernel Principal Component Analysis Michael E. Tipping

Sparsity of Data Representation of Optimal Kernel Machine and Leave-one-out Estimator Adam Kowalczyk

Rate-coded Restricted Boltzmann Machines for Face Recognition Yee Whye Teh, Geoffrey E. Hinton

Shape Context: A New Descriptor for Shape Matching and Object Recognition Serge Belongie, Jitendra Malik, Jan Puzicha

Position Variance, Recurrence and Perceptual Learning Zhaoping Li, Peter Dayan

Permitted and Forbidden Sets in Symmetric Threshold-Linear Networks Richard H. R. Hahnloser, H. Sebastian Seung

Competition and Arbors in Ocular Dominance Peter Dayan

Learning Switching Linear Models of Human Motion Vladimir Pavlovic, James M. Rehg, John MacCormick

New Approaches Towards Robust and Adaptive Speech Recognition Hervé Bourlard, Samy Bengio, Katrin Weber

Place Cells and Spatial Navigation Based on 2D Visual Feature Extraction, Path Integration, and Reinforcement Learning Angelo Arleo, Fabrizio Smeraldi, Stéphane Hug, Wulfram Gerstner

Kernel-Based Reinforcement Learning in Average-Cost Problems: An Application to Optimal Portfolio Choice Dirk Ormoneit, Peter W. Glynn

A New Approximate Maximal Margin Classification Algorithm Claudio Gentile

Ensemble Learning and Linear Response Theory for ICA Pedro A. d. F. R. Højen-Sørensen, Ole Winther, Lars Kai Hansen

Regularization with Dot-Product Kernels Alex J. Smola, Zoltán L. Óvári, Robert C. Williamson

From Margin to Sparsity Thore Graepel, Ralf Herbrich, Robert C. Williamson

On a Connection between Kernel PCA and Metric Multidimensional Scaling Christopher K. I. Williams

One Microphone Source Separation Sam T. Roweis

Interactive Parts Model: An Application to Recognition of On-line Cursive Script Predrag Neskovic, Philip C. Davis, Leon N. Cooper

A New Model of Spatial Representation in Multimodal Brain Areas Sophie Denève, Jean-René Duhamel, Alexandre Pouget

Feature Correspondence: A Markov Chain Monte Carlo Approach Frank Dellaert, Steven M. Seitz, Sebastian Thrun, Charles E. Thorpe

Stagewise Processing in Error-correcting Codes and Image Restoration K. Y. Michael Wong, Hidetoshi Nishimori

The Kernel Gibbs Sampler Thore Graepel, Ralf Herbrich

Learning Sparse Image Codes using a Wavelet Pyramid Architecture Bruno A. Olshausen, Phil Sallee, Michael S. Lewicki

Weak Learners and Improved Rates of Convergence in Boosting Shie Mannor, Ron Meir

Keeping Flexible Active Contours on Track using Metropolis Updates Trausti T. Kristjansson, Brendan J. Frey

Data Clustering by Markovian Relaxation and the Information Bottleneck Method Naftali Tishby, Noam Slonim

Balancing Multiple Sources of Reward in Reinforcement Learning Christian R. Shelton

Temporally Dependent Plasticity: An Information Theoretic Account Gal Chechik, Naftali Tishby

Analysis of Bit Error Probability of Direct-Sequence CDMA Multiuser Demodulators Toshiyuki Tanaka

A Variational Mean-Field Theory for Sigmoidal Belief Networks Chiranjib Bhattacharyya, S. Sathiya Keerthi

Robust Reinforcement Learning Jun Morimoto, Kenji Doya

Explaining Away in Weight Space Peter Dayan, Sham Kakade

Improved Output Coding for Classification Using Continuous Relaxation Koby Crammer, Yoram Singer

Learning Curves for Gaussian Processes Regression: A Framework for Good Approximations Dörthe Malzahn, Manfred Opper

Sequentially Fitting

Inclusive'' Trees for Inference in Noisy-OR Networks Brendan J. Frey, Relu Patrascu, Tommi Jaakkola, Jodi Moran

Whence Sparseness? Carl van Vreeswijk

Periodic Component Analysis: An Eigenvalue Method for Representing Periodic Structure in Speech Lawrence K. Saul, Jont B. Allen

Partially Observable SDE Models for Image Sequence Recognition Tasks Javier R. Movellan, Paul Mineiro, Ruth J. Williams

Combining ICA and Top-Down Attention for Robust Speech Recognition Un-Min Bae, Soo-Young Lee

A Comparison of Image Processing Techniques for Visual Speech Recognition Applications Michael S. Gray, Terrence J. Sejnowski, Javier R. Movellan

Learning Continuous Distributions: Simulations With Field Theoretic Priors Ilya Nemenman, William Bialek

Algebraic Information Geometry for Learning Machines with Singularities Sumio Watanabe

The Missing Link - A Probabilistic Model of Document Content and Hypertext Connectivity David A. Cohn, Thomas Hofmann

The Use of Classifiers in Sequential Inference Vasin Punyakanok, Dan Roth

Finding the Key to a Synapse Thomas Natschläger, Wolfgang Maass

The Unscented Particle Filter Rudolph van der Merwe, Arnaud Doucet, Nando de Freitas, Eric A. Wan

Algorithms for Non-negative Matrix Factorization Daniel D. Lee, H. Sebastian Seung

Divisive and Subtractive Mask Effects: Linking Psychophysics and Biophysics Barbara Zenger, Christof Koch

Factored Semi-Tied Covariance Matrices Mark J. F. Gales

Noise Suppression Based on Neurophysiologically-motivated SNR Estimation for Robust Speech Recognition Jürgen Tchorz, Michael Kleinschmidt, Birger Kollmeier

Dendritic Compartmentalization Could Underlie Competition and Attentional Biasing of Simultaneous Visual Stimuli Kevin A. Archie, Bartlett W. Mel

Smart Vision Chip Fabricated Using Three Dimensional Integration Technology Hiroyuki Kurino, M. Nakagawa, Kang Wook Lee, Tomonori Nakamura, Yuusuke Yamada, Ki Tae Park, Mitsumasa Koyanagi

A Productive, Systematic Framework for the Representation of Visual Structure Shimon Edelman, Nathan Intrator

Advances in Neural Information Processing Systems 13 (NIPS 2000)

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