Advances in Neural Information Processing Systems 13 (NIPS 2000)

• 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 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. 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 Leisink, Hilbert Kappen
• Occam's Razor Carl Rasmussen, Zoubin Ghahramani
• Exact Solutions to Time-Dependent MDPs Justin Boyan, Michael Littman
• An Information Maximization Approach to Overcomplete and Recurrent Representations Oren Shriki, Haim Sompolinsky, Daniel Lee
• A Linear Programming Approach to Novelty Detection Colin Campbell, Kristin Bennett
• Programmable Reinforcement Learning Agents David Andre, Stuart Russell
• Learning Joint Statistical Models for Audio-Visual Fusion and Segregation John W. Fisher III, Trevor Darrell, William Freeman, Paul 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 Brown, Christophe Giraud-Carrier
• High-temperature Expansions for Learning Models of Nonnegative Data Oliver Downs
• A Support Vector Method for Clustering Asa Ben-Hur, David Horn, Hava Siegelmann, Vladimir Vapnik
• Incremental and Decremental Support Vector Machine Learning Gert Cauwenberghs, Tomaso Poggio
• Active Inference in Concept Learning Jonathan Nelson, Javier Movellan
• The Interplay of Symbolic and Subsymbolic Processes in Anagram Problem Solving David Grimes, Michael C. Mozer
• Using the Nyström Method to Speed Up Kernel Machines Christopher 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 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 Smola, Peter Bartlett
• Large Scale Bayes Point Machines Ralf Herbrich, Thore Graepel
• Efficient Learning of Linear Perceptrons Shai Ben-David, Hans-Ulrich Simon
• Gaussianization Scott Chen, Ramesh 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 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 Hertz
• On Reversing Jensen's Inequality Tony Jebara, Alex Pentland
• From Mixtures of Mixtures to Adaptive Transform Coding Cynthia Archer, Todd 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 Parra, Clay Spence, Paul Sajda
• Probabilistic Semantic Video Indexing Milind 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 Barto
• Structure Learning in Human Causal Induction Joshua Tenenbaum, Thomas 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 van Steveninck, William Bialek
• Generalized Belief Propagation Jonathan S. Yedidia, William Freeman, Yair Weiss
• Multiple Timescales of Adaptation in a Neural Code Adrienne Fairhall, Geoffrey Lewen, William Bialek, Robert van Steveninck
• Speech Denoising and Dereverberation Using Probabilistic Models Hagai Attias, John 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 Tjan
• Text Classification using String Kernels Huma Lodhi, John Shawe-Taylor, Nello Cristianini, Christopher Watkins
• Model Complexity, Goodness of Fit and Diminishing Returns Igor Cadez, Padhraic Smyth
• Fast Training of Support Vector Classifiers Fernando Pérez-Cruz, Pedro 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 C. Mozer
• A Neural Probabilistic Language Model Yoshua Bengio, Réjean Ducharme, Pascal Vincent
• Support Vector Novelty Detection Applied to Jet Engine Vibration Spectra Paul Hayton, Bernhard Schölkopf, Lionel Tarassenko, Paul Anuzis
• `N-Body' Problems in Statistical Learning Alexander Gray, Andrew Moore
• A Silicon Primitive for Competitive Learning David Hsu, Miguel Figueroa, Chris Diorio
• Automatic Choice of Dimensionality for PCA Thomas Minka
• Propagation Algorithms for Variational Bayesian Learning Zoubin Ghahramani, Matthew 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 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 Brown
• Constrained Independent Component Analysis Wei Lu, Jagath Rajapakse
• A Gradient-Based Boosting Algorithm for Regression Problems Richard Zemel, Toniann Pitassi
• The Early Word Catches the Weights Mark Smith, Garrison Cottrell, Karen Anderson
• The Manhattan World Assumption: Regularities in Scene Statistics which Enable Bayesian Inference James Coughlan, Alan L. Yuille
• Processing of Time Series by Neural Circuits with Biologically Realistic Synaptic Dynamics Thomas Natschläger, Wolfgang Maass, Eduardo Sontag, Anthony Zador
• Machine Learning for Video-Based Rendering Arno Schödl, Irfan 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 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 Fairhall, William Bialek
• Tree-Based Modeling and Estimation of Gaussian Processes on Graphs with Cycles Martin J. Wainwright, Erik Sudderth, Alan Willsky
• Learning Winner-take-all Competition Between Groups of Neurons in Lateral Inhibitory Networks Xiaohui Xie, Richard Hahnloser, H. Sebastian Seung
• Foundations for a Circuit Complexity Theory of Sensory Processing Robert 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 Black, Trevor Hastie
• The Use of MDL to Select among Computational Models of Cognition In Myung, Mark Pitt, Shaobo Zhang, Vijay Balasubramanian
• Active Support Vector Machine Classification Olvi Mangasarian, David 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 Hansen, Stephen Strother
• Vicinal Risk Minimization Olivier Chapelle, Jason Weston, Léon Bottou, Vladimir Vapnik
• Sparse Kernel Principal Component Analysis Michael 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 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 Højen-Sørensen, Ole Winther, Lars Hansen
• Regularization with Dot-Product Kernels Alex Smola, Zoltán 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 Williams
• One Microphone Source Separation Sam Roweis
• Interactive Parts Model: An Application to Recognition of On-line Cursive Script Predrag Neskovic, Philip Davis, Leon 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 Seitz, Sebastian Thrun, Charles 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 Olshausen, Phil Sallee, Michael Lewicki
• Weak Learners and Improved Rates of Convergence in Boosting Shie Mannor, Ron Meir
• Keeping Flexible Active Contours on Track using Metropolis Updates Trausti 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 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. 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 Saul, Jont Allen
• Partially Observable SDE Models for Image Sequence Recognition Tasks Javier Movellan, Paul Mineiro, Ruth 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 Gray, Terrence J. Sejnowski, Javier 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 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 Wan
• Algorithms for Non-negative Matrix Factorization Daniel Lee, H. Sebastian Seung
• Divisive and Subtractive Mask Effects: Linking Psychophysics and Biophysics Barbara Zenger, Christof Koch
• Factored Semi-Tied Covariance Matrices Mark 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 Archie, Bartlett Mel
• Smart Vision Chip Fabricated Using Three Dimensional Integration Technology Hiroyuki Kurino, M. Nakagawa, Kang Lee, Tomonori Nakamura, Yuusuke Yamada, Ki Park, Mitsumasa Koyanagi
• A Productive, Systematic Framework for the Representation of Visual Structure Shimon Edelman, Nathan Intrator