NIPS 2000 Proceedings

Advances in Neural Information Processing Systems 13 (NIPS 2000)

The papers below appear in Advances in Neural Information Processing Systems 13 edited by T.K. Leen and T.G. Dietterich and V. Tresp.
They are proceedings from the conference, "Neural Information Processing Systems 2000."

Who Does What? A Novel Algorithm to Determine Function Localization Ranit Aharonov-Barki, Isaac Meilijson, Eytan Ruppin
A Productive, Systematic Framework for the Representation of Visual Structure Shimon Edelman, Nathan Intrator
The Interplay of Symbolic and Subsymbolic Processes in Anagram Problem Solving David B. Grimes, Michael C. Mozer
Hippocampally-Dependent Consolidation in a Hierarchical Model of Neocortex Szabolcs Káli, Peter Dayan
Position Variance, Recurrence and Perceptual Learning Zhaoping Li, Peter Dayan
The Use of MDL to Select among Computational Models of Cognition In Jae Myung, Mark A. Pitt, Shaobo Zhang, Vijay Balasubramanian
Active Inference in Concept Learning Jonathan D. Nelson, Javier R. Movellan
The Early Word Catches the Weights Mark A. Smith, Garrison W. Cottrell, Karen L. Anderson
Structure Learning in Human Causal Induction Joshua B. Tenenbaum, Thomas L. Griffiths
Adaptive Object Representation with Hierarchically-Distributed Memory Sites Bosco S. Tjan
What Can a Single Neuron Compute? Blaise Agüera y Arcas, Adrienne L. Fairhall, William Bialek
Dendritic Compartmentalization Could Underlie Competition and Attentional Biasing of Simultaneous Visual Stimuli Kevin A. Archie, Bartlett W. Mel
Place Cells and Spatial Navigation Based on 2D Visual Feature Extraction, Path Integration, and Reinforcement Learning Angelo Arleo, Fabrizio Smeraldi, Stéphane Hug, Wulfram Gerstner
Modelling Spatial Recall, Mental Imagery and Neglect Suzanna Becker, Neil Burgess
Stability and Noise in Biochemical Switches William Bialek
Temporally Dependent Plasticity: An Information Theoretic Account Gal Chechik, Naftali Tishby
A New Model of Spatial Representation in Multimodal Brain Areas Sophie Denève, Jean-René Duhamel, Alexandre Pouget
Multiple Timescales of Adaptation in a Neural Code Adrienne L. Fairhall, Geoffrey D. Lewen, William Bialek, Robert R. de Ruyter van Steveninck
Dopamine Bonuses Sham Kakade, Peter Dayan
Finding the Key to a Synapse Thomas Natschläger, Wolfgang Maass
Processing of Time Series by Neural Circuits with Biologically Realistic Synaptic Dynamics Thomas Natschläger, Wolfgang Maass, Eduardo D. Sontag, Anthony M. Zador
Spike-Timing-Dependent Learning for Oscillatory Networks Silvia Scarpetta, Zhaoping Li, John A. Hertz
Universality and Individuality in a Neural Code Elad Schneidman, Naama Brenner, Naftali Tishby, Robert R. de Ruyter van Steveninck, William Bialek
Natural Sound Statistics and Divisive Normalization in the Auditory System Odelia Schwartz, Eero P. Simoncelli
Whence Sparseness? Carl van Vreeswijk
Efficient Learning of Linear Perceptrons Shai Ben-David, Hans-Ulrich Simon
Algorithmic Stability and Generalization Performance Olivier Bousquet, André Elisseeff
Competition and Arbors in Ocular Dominance Peter Dayan
From Margin to Sparsity Thore Graepel, Ralf Herbrich, Robert C. Williamson
Permitted and Forbidden Sets in Symmetric Threshold-Linear Networks Richard H. R. Hahnloser, H. Sebastian Seung
A PAC-Bayesian Margin Bound for Linear Classifiers: Why SVMs work Ralf Herbrich, Thore Graepel
On Reversing Jensen's Inequality Tony Jebara, Alex Pentland
Second Order Approximations for Probability Models Hilbert J. Kappen, Wim Wiegerinck
Some New Bounds on the Generalization Error of Combined Classifiers Vladimir Koltchinskii, Dmitriy Panchenko, Fernando Lozano
Sparsity of Data Representation of Optimal Kernel Machine and Leave-one-out Estimator Adam Kowalczyk
Foundations for a Circuit Complexity Theory of Sensory Processing Robert A. Legenstein, Wolfgang Maass
A Tighter Bound for Graphical Models Martijn A. R. Leisink, Hilbert J. Kappen
Learning Curves for Gaussian Processes Regression: A Framework for Good Approximations Dörthe Malzahn, Manfred Opper
Weak Learners and Improved Rates of Convergence in Boosting Shie Mannor, Ron Meir
Learning Continuous Distributions: Simulations With Field Theoretic Priors Ilya Nemenman, William Bialek
Occam's Razor Carl Edward Rasmussen, Zoubin Ghahramani
The Kernel Trick for Distances Bernhard Schölkopf
Regularization with Dot-Product Kernels Alex J. Smola, Zoltán L. Óvári, Robert C. Williamson
Analysis of Bit Error Probability of Direct-Sequence CDMA Multiuser Demodulators Toshiyuki Tanaka
Error-correcting Codes on a Bethe-like Lattice Renato Vicente, David Saad, Yoshiyuki Kabashima
Algebraic Information Geometry for Learning Machines with Singularities Sumio Watanabe
Computing with Finite and Infinite Networks Ole Winther
Stagewise Processing in Error-correcting Codes and Image Restoration K. Y. Michael Wong, Hidetoshi Nishimori
Learning Winner-take-all Competition Between Groups of Neurons in Lateral Inhibitory Networks Xiaohui Xie, Richard H. R. Hahnloser, H. Sebastian Seung
Convergence of Large Margin Separable Linear Classification Tong Zhang
A Support Vector Method for Clustering Asa Ben-Hur, David Horn, Hava T. Siegelmann, Vladimir Vapnik
A Variational Mean-Field Theory for Sigmoidal Belief Networks Chiranjib Bhattacharyya, S. Sathiya Keerthi
Direct Classification with Indirect Data Timothy X. Brown
Model Complexity, Goodness of Fit and Diminishing Returns Igor V. Cadez, Padhraic Smyth
A Linear Programming Approach to Novelty Detection Colin Campbell, Kristin P. Bennett
Overfitting in Neural Nets: Backpropagation, Conjugate Gradient, and Early Stopping Rich Caruana, Steve Lawrence, C. Lee Giles
Incremental and Decremental Support Vector Machine Learning Gert Cauwenberghs, Tomaso Poggio
Vicinal Risk Minimization Olivier Chapelle, Jason Weston, Léon Bottou, Vladimir Vapnik
Gaussianization Scott Saobing Chen, Ramesh A. Gopinath
The Missing Link - A Probabilistic Model of Document Content and Hypertext Connectivity David A. Cohn, Thomas Hofmann
Improved Output Coding for Classification Using Continuous Relaxation Koby Crammer, Yoram Singer
Sparse Representation for Gaussian Process Models Lehel Csató, Manfred Opper
Explaining Away in Weight Space Peter Dayan, Sham Kakade
An Adaptive Metric Machine for Pattern Classification Carlotta Domeniconi, Jing Peng, Dimitrios Gunopulos
High-temperature Expansions for Learning Models of Nonnegative Data Oliver B. Downs
Incorporating Second-Order Functional Knowledge for Better Option Pricing Charles Dugas, Yoshua Bengio, François Bélisle, Claude Nadeau, René Garcia
Discovering Hidden Variables: A Structure-Based Approach Gal Elidan, Noam Lotner, Nir Friedman, Daphne Koller
Accumulator Networks: Suitors of Local Probability Propagation Brendan J. Frey, Anitha Kannan
Sequentially Fitting ``Inclusive'' Trees for Inference in Noisy-OR Networks Brendan J. Frey, Relu Patrascu, Tommi Jaakkola, Jodi Moran
A New Approximate Maximal Margin Classification Algorithm Claudio Gentile
Propagation Algorithms for Variational Bayesian Learning Zoubin Ghahramani, Matthew J. Beal
The Kernel Gibbs Sampler Thore Graepel, Ralf Herbrich
`N-Body' Problems in Statistical Learning Alexander G. Gray, Andrew W. Moore
Large Scale Bayes Point Machines Ralf Herbrich, Thore Graepel
Beyond Maximum Likelihood and Density Estimation: A Sample-Based Criterion for Unsupervised Learning of Complex Models Sepp Hochreiter, Michael C. Mozer
Ensemble Learning and Linear Response Theory for ICA Pedro A. d. F. R. Højen-Sørensen, Ole Winther, Lars Kai Hansen
Generalizable Singular Value Decomposition for Ill-posed Datasets Ulrik Kjems, Lars Kai Hansen, Stephen C. Strother
Algorithms for Non-negative Matrix Factorization Daniel D. Lee, H. Sebastian Seung
Text Classification using String Kernels Huma Lodhi, John Shawe-Taylor, Nello Cristianini, Christopher J. C. H. Watkins
Constrained Independent Component Analysis Wei Lu, Jagath C. Rajapakse
Active Support Vector Machine Classification Olvi L. Mangasarian, David R. Musicant
The Unscented Particle Filter Rudolph van der Merwe, Arnaud Doucet, Nando de Freitas, Eric A. Wan
A Mathematical Programming Approach to the Kernel Fisher Algorithm Sebastian Mika, Gunnar Rätsch, Klaus-Robert Müller
Automatic Choice of Dimensionality for PCA Thomas P. Minka
On Iterative Krylov-Dogleg Trust-Region Steps for Solving Neural Networks Nonlinear Least Squares Problems Eiji Mizutani, James Demmel
An Information Maximization Approach to Overcomplete and Recurrent Representations Oren Shriki, Haim Sompolinsky, Daniel D. Lee
Sparse Greedy Gaussian Process Regression Alex J. Smola, Peter L. Bartlett
Kernel Expansions with Unlabeled Examples Martin Szummer, Tommi Jaakkola
Sparse Kernel Principal Component Analysis Michael E. Tipping
Data Clustering by Markovian Relaxation and the Information Bottleneck Method Naftali Tishby, Noam Slonim
Active Learning for Parameter Estimation in Bayesian Networks Simon Tong, Daphne Koller
Mixtures of Gaussian Processes Volker Tresp
Tree-Based Modeling and Estimation of Gaussian Processes on Graphs with Cycles Martin J. Wainwright, Erik B. Sudderth, Alan S. Willsky
Feature Selection for SVMs Jason Weston, Sayan Mukherjee, Olivier Chapelle, Massimiliano Pontil, Tomaso Poggio, Vladimir Vapnik
On a Connection between Kernel PCA and Metric Multidimensional Scaling Christopher K. I. Williams
Using the Nyström Method to Speed Up Kernel Machines Christopher K. I. Williams, Matthias Seeger
Generalized Belief Propagation Jonathan S. Yedidia, William T. Freeman, Yair Weiss
A Gradient-Based Boosting Algorithm for Regression Problems Richard S. Zemel, Toniann Pitassi
Regularized Winnow Methods Tong Zhang
A Silicon Primitive for Competitive Learning David Hsu, Miguel Figueroa, Chris Diorio
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
Homeostasis in a Silicon Integrate and Fire Neuron Shih-Chii Liu, Bradley A. Minch
Fast Training of Support Vector Classifiers Fernando Pérez-Cruz, Pedro Luis Alarcón-Diana, Angel Navia-Vázquez, Antonio Artés-Rodríguez
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
New Approaches Towards Robust and Adaptive Speech Recognition Hervé Bourlard, Samy Bengio, Katrin Weber
Speech Denoising and Dereverberation Using Probabilistic Models Hagai Attias, John C. Platt, Alex Acero, Li Deng
Combining ICA and Top-Down Attention for Robust Speech Recognition Un-Min Bae, Soo-Young Lee
Learning Joint Statistical Models for Audio-Visual Fusion and Segregation John W. Fisher III, Trevor Darrell, William T. Freeman, Paul A. Viola
Factored Semi-Tied Covariance Matrices Mark J. F. Gales
Higher-Order Statistical Properties Arising from the Non-Stationarity of Natural Signals Lucas C. Parra, Clay Spence, Paul Sajda
One Microphone Source Separation Sam T. Roweis
Minimum Bayes Error Feature Selection for Continuous Speech Recognition George Saon, Mukund Padmanabhan
Periodic Component Analysis: An Eigenvalue Method for Representing Periodic Structure in Speech Lawrence K. Saul, Jont B. Allen
FaceSync: A Linear Operator for Measuring Synchronization of Video Facial Images and Audio Tracks Malcolm Slaney, Michele Covell
Noise Suppression Based on Neurophysiologically-motivated SNR Estimation for Robust Speech Recognition Jürgen Tchorz, Michael Kleinschmidt, Birger Kollmeier
Shape Context: A New Descriptor for Shape Matching and Object Recognition Serge Belongie, Jitendra Malik, Jan Puzicha
Emergence of Movement Sensitive Neurons' Properties by Learning a Sparse Code for Natural Moving Images Rafal Bogacz, Malcolm W. Brown, Christophe G. Giraud-Carrier
The Manhattan World Assumption: Regularities in Scene Statistics which Enable Bayesian Inference James M. Coughlan, Alan L. Yuille
Feature Correspondence: A Markov Chain Monte Carlo Approach Frank Dellaert, Steven M. Seitz, Sebastian Thrun, Charles E. Thorpe
Keeping Flexible Active Contours on Track using Metropolis Updates Trausti T. Kristjansson, Brendan J. Frey
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
Partially Observable SDE Models for Image Sequence Recognition Tasks Javier R. Movellan, Paul Mineiro, Ruth J. Williams
Learning Sparse Image Codes using a Wavelet Pyramid Architecture Bruno A. Olshausen, Phil Sallee, Michael S. Lewicki
Learning and Tracking Cyclic Human Motion Dirk Ormoneit, Hedvig Sidenbladh, Michael J. Black, Trevor Hastie
Redundancy and Dimensionality Reduction in Sparse-Distributed Representations of Natural Objects in Terms of Their Local Features Penio S. Penev
Rate-coded Restricted Boltzmann Machines for Face Recognition Yee Whye Teh, Geoffrey E. Hinton
Divisive and Subtractive Mask Effects: Linking Psychophysics and Biophysics Barbara Zenger, Christof Koch
From Mixtures of Mixtures to Adaptive Transform Coding Cynthia Archer, Todd K. Leen
A Neural Probabilistic Language Model Yoshua Bengio, Réjean Ducharme, Pascal Vincent
A Comparison of Image Processing Techniques for Visual Speech Recognition Applications Michael S. Gray, Terrence J. Sejnowski, Javier R. Movellan
Support Vector Novelty Detection Applied to Jet Engine Vibration Spectra Paul M. Hayton, Bernhard Schölkopf, Lionel Tarassenko, Paul Anuzis
Recognizing Hand-written Digits Using Hierarchical Products of Experts Guy Mayraz, Geoffrey E. Hinton
Sex with Support Vector Machines Baback Moghaddam, Ming-Hsuan Yang
Probabilistic Semantic Video Indexing Milind R. Naphade, Igor Kozintsev, Thomas S. Huang
Interactive Parts Model: An Application to Recognition of On-line Cursive Script Predrag Neskovic, Philip C. Davis, Leon N. Cooper
Learning Switching Linear Models of Human Motion Vladimir Pavlovic, James M. Rehg, John MacCormick
Bayes Networks on Ice: Robotic Search for Antarctic Meteorites Liam Pedersen, Dimitrios Apostolopoulos, William Whittaker
The Use of Classifiers in Sequential Inference Vasin Punyakanok, Dan Roth
Machine Learning for Video-Based Rendering Arno Schödl, Irfan A. Essa
Bayesian Video Shot Segmentation Nuno Vasconcelos, Andrew Lippman
Programmable Reinforcement Learning Agents David Andre, Stuart J. Russell
Exact Solutions to Time-Dependent MDPs Justin A. Boyan, Michael L. Littman
Decomposition of Reinforcement Learning for Admission Control of Self-Similar Call Arrival Processes Jakob Carlström
Reinforcement Learning with Function Approximation Converges to a Region Geoffrey J. Gordon
Hierarchical Memory-Based Reinforcement Learning Natalia Hernandez-Gardiol, Sridhar Mahadevan
Automated State Abstraction for Options using the U-Tree Algorithm Anders Jonsson, Andrew G. Barto
Robust Reinforcement Learning Jun Morimoto, Kenji Doya
Kernel-Based Reinforcement Learning in Average-Cost Problems: An Application to Optimal Portfolio Choice Dirk Ormoneit, Peter W. Glynn
Using Free Energies to Represent Q-values in a Multiagent Reinforcement Learning Task Brian Sallans, Geoffrey E. Hinton
Balancing Multiple Sources of Reward in Reinforcement Learning Christian R. Shelton
APRICODD: Approximate Policy Construction Using Decision Diagrams Robert St-Aubin, Jesse Hoey, Craig Boutilier