NeurIPS 2001

197 papers

(Not) Bounding the True Error John Langford, Rich Caruana

3 State Neurons for Contextual Processing Ádám Kepecs, S. Raghavachari

A Bayesian Model Predicts Human Parse Preference and Reading Times in Sentence Processing S. Narayanan, Daniel Jurafsky

A Bayesian Network for Real-Time Musical Accompaniment Christopher Raphael

A Dynamic HMM for On-Line Segmentation of Sequential Data Jens Kohlmorgen, Steven Lemm

A General Greedy Approximation Algorithm with Applications T. Zhang

A Generalization of Principal Components Analysis to the Exponential Family Michael Collins, S. Dasgupta, Robert E. Schapire

A Hierarchical Model of Complex Cells in Visual Cortex for the Binocular Perception of Motion-in-Depth Silvio P. Sabatini, Fabio Solari, Giulia Andreani, Chiara Bartolozzi, Giacomo M. Bisio

A Kernel Method for Multi-Labelled Classification André Elisseeff, Jason Weston

A Maximum-Likelihood Approach to Modeling Multisensory Enhancement H. Colonius, A. Diederich

A Model of the Phonological Loop: Generalization and Binding Randall C. O'Reilly, R. Soto

A Natural Policy Gradient Sham M. Kakade

A Neural Oscillator Model of Auditory Selective Attention Stuart N. Wrigley, Guy J. Brown

A New Discriminative Kernel from Probabilistic Models Koji Tsuda, Motoaki Kawanabe, Gunnar Rätsch, Sören Sonnenburg, Klaus-Robert Müller

A Parallel Mixture of SVMs for Very Large Scale Problems Ronan Collobert, Samy Bengio, Yoshua Bengio

A Quantitative Model of Counterfactual Reasoning Daniel Yarlett, Michael Ramscar

A Rational Analysis of Cognitive Control in a Speeded Discrimination Task Michael Mozer, Michael D. Colagrosso, David E. Huber

A Rotation and Translation Invariant Discrete Saliency Network Lance R. Williams, John W. Zweck

A Sequence Kernel and Its Application to Speaker Recognition William M. Campbell

A Theory of Neural Integration in the Head-Direction System Richard Hahnloser, Xiaohui Xie, H. S. Seung

A Variational Approach to Learning Curves Dörthe Malzahn, Manfred Opper

ACh, Uncertainty, and Cortical Inference Peter Dayan, Angela J. Yu

Active Information Retrieval Tommi Jaakkola, Hava T. Siegelmann

Active Learning in the Drug Discovery Process Manfred K. Warmuth, Gunnar Rätsch, Michael Mathieson, Jun Liao, Christian Lemmen

Active Portfolio-Management Based on Error Correction Neural Networks Hans-Georg Zimmermann, Ralph Neuneier, Ralph Grothmann

Activity Driven Adaptive Stochastic Resonance Gregor Wenning, Klaus Obermayer

Adaptive Nearest Neighbor Classification Using Support Vector Machines Carlotta Domeniconi, Dimitrios Gunopulos

Adaptive Sparseness Using Jeffreys Prior Mário Figueiredo

Agglomerative Multivariate Information Bottleneck Noam Slonim, Nir Friedman, Naftali Tishby

ALGONQUIN - Learning Dynamic Noise Models from Noisy Speech for Robust Speech Recognition Brendan J. Frey, Trausti T. Kristjansson, Li Deng, Alex Acero

Algorithmic Luckiness Ralf Herbrich, Robert C. Williamson

An Efficient Clustering Algorithm Using Stochastic Association Model and Its Implementation Using Nanostructures Takashi Morie, Tomohiro Matsuura, Makoto Nagata, Atsushi Iwata

An Efficient, Exact Algorithm for Solving Tree-Structured Graphical Games Michael L. Littman, Michael J. Kearns, Satinder P. Singh

Analog Soft-Pattern-Matching Classifier Using Floating-Gate MOS Technology Toshihiko Yamasaki, Tadashi Shibata

Analysis of Sparse Bayesian Learning Anita C. Faul, Michael E. Tipping

Approximate Dynamic Programming via Linear Programming Daniela Farias, Benjamin V. Roy

Associative Memory in Realistic Neuronal Networks Peter E. Latham

Asymptotic Universality for Learning Curves of Support Vector Machines Manfred Opper, Robert Urbanczik

Audio-Visual Sound Separation via Hidden Markov Models John R. Hershey, Michael Casey

Batch Value Function Approximation via Support Vectors Thomas G. Dietterich, Xin Wang

Bayesian Morphometry of Hippocampal Cells Suggests Same-Cell Somatodendritic Repulsion Giorgio A. Ascoli, Alexei V. Samsonovich

Bayesian Predictive Profiles with Applications to Retail Transaction Data Igor V. Cadez, Padhraic Smyth

Bayesian Time Series Classification Peter Sykacek, Stephen J. Roberts

Blind Source Separation via Multinode Sparse Representation Michael Zibulevsky, Pavel Kisilev, Yehoshua Y. Zeevi, Barak A. Pearlmutter

Boosting and Maximum Likelihood for Exponential Models Guy Lebanon, John D. Lafferty

Categorization by Learning and Combining Object Parts Bernd Heisele, Thomas Serre, Massimiliano Pontil, Thomas Vetter, Tomaso Poggio

Causal Categorization with Bayes Nets Bob Rehder

Characterizing Neural Gain Control Using Spike-Triggered Covariance Odelia Schwartz, E. J. Chichilnisky, Eero P. Simoncelli

Citcuits for VLSI Implementation of Temporally Asymmetric Hebbian Learning A. Bofill, D. P. Thompson, Alan F. Murray

Classifying Single Trial EEG: Towards Brain Computer Interfacing Benjamin Blankertz, Gabriel Curio, Klaus-Robert Müller

Cobot: A Social Reinforcement Learning Agent Charles Lee Isbell Jr., Christian R. Shelton

Computing Time Lower Bounds for Recurrent Sigmoidal Neural Networks M. Schmitt

Constructing Distributed Representations Using Additive Clustering Wheeler Ruml

Contextual Modulation of Target Saliency Antonio Torralba

Convergence of Optimistic and Incremental Q-Learning Eyal Even-dar, Yishay Mansour

Convolution Kernels for Natural Language Michael Collins, Nigel Duffy

Correlation Codes in Neuronal Populations Maoz Shamir, Haim Sompolinsky

Covariance Kernels from Bayesian Generative Models Matthias Seeger

Direct Value-Approximation for Factored MDPs Dale Schuurmans, Relu Patrascu

Discriminative Direction for Kernel Classifiers Polina Golland

Distribution of Mutual Information Marcus Hutter

Duality, Geometry, and Support Vector Regression J. Bi, Kristin P. Bennett

Dynamic Time-Alignment Kernel in Support Vector Machine Hiroshi Shimodaira, Ken-ichi Noma, Mitsuru Nakai, Shigeki Sagayama

Effective Size of Receptive Fields of Inferior Temporal Visual Cortex Neurons in Natural Scenes Thomas P. Trappenberg, Edmund T. Rolls, Simon M. Stringer

Efficiency Versus Convergence of Boolean Kernels for On-Line Learning Algorithms Roni Khardon, Dan Roth, Rocco A. Servedio

Efficient Resources Allocation for Markov Decision Processes Rémi Munos

EM-DD: An Improved Multiple-Instance Learning Technique Qi Zhang, Sally A. Goldman

Entropy and Inference, Revisited Ilya Nemenman, F. Shafee, William Bialek

Escaping the Convex Hull with Extrapolated Vector Machines Patrick Haffner

Estimating Car Insurance Premia: A Case Study in High-Dimensional Data Inference Nicolas Chapados, Yoshua Bengio, Pascal Vincent, Joumana Ghosn, Charles Dugas, Ichiro Takeuchi, Linyan Meng

Estimating the Reliability of ICA Projections Frank C. Meinecke, Andreas Ziehe, Motoaki Kawanabe, Klaus-Robert Müller

Exact Differential Equation Population Dynamics for Integrate-and-Fire Neurons Julian Eggert, Berthold Bäuml

Eye Movements and the Maturation of Cortical Orientation Selectivity Antonino Casile, Michele Rucci

Face Recognition Using Kernel Methods Ming-Hsuan Yang

Fast and Robust Classification Using Asymmetric AdaBoost and a Detector Cascade Paul Viola, Michael Jones

Fast Parameter Estimation Using Green's Functions K. Wong, F. Li

Fast, Large-Scale Transformation-Invariant Clustering Brendan J. Frey, Nebojsa Jojic

Fragment Completion in Humans and Machines David Jacobs, Bas Rokers, Archisman Rudra, Zili Liu

Gaussian Process Regression with Mismatched Models Peter Sollich

Generalizable Relational Binding from Coarse-Coded Distributed Representations Randall C. O'Reilly, R. S. Busby

Generalization Performance of Some Learning Problems in Hilbert Functional Spaces T. Zhang

Generating Velocity Tuning by Asymmetric Recurrent Connections Xiaohui Xie, Martin A. Giese

Geometrical Singularities in the Neuromanifold of Multilayer Perceptrons Shun-ichi Amari, Hyeyoung Park, Tomoko Ozeki

Global Coordination of Local Linear Models Sam T. Roweis, Lawrence K. Saul, Geoffrey E. Hinton

Grammar Transfer in a Second Order Recurrent Neural Network Michiro Negishi, Stephen J. Hanson

Grammatical Bigrams Mark A. Paskin

Group Redundancy Measures Reveal Redundancy Reduction in the Auditory Pathway Gal Chechik, Amir Globerson, M. J. Anderson, E. D. Young, Israel Nelken, Naftali Tishby

Grouping and Dimensionality Reduction by Locally Linear Embedding Marzia Polito, Pietro Perona

Grouping with Bias Stella X. Yu, Jianbo Shi

Hyperbolic Self-Organizing Maps for Semantic Navigation Jorg Ontrup, Helge Ritter

Improvisation and Learning Judy A Franklin

Incorporating Invariances in Non-Linear Support Vector Machines Olivier Chapelle, Bernhard Schölkopf

Incremental A* S. Koenig, M. Likhachev

Incremental Learning and Selective Sampling via Parametric Optimization Framework for SVM Shai Fine, Katya Scheinberg

Infinite Mixtures of Gaussian Process Experts Carl E. Rasmussen, Zoubin Ghahramani

Information Geometrical Framework for Analyzing Belief Propagation Decoder Shiro Ikeda, Toshiyuki Tanaka, Shun-ichi Amari

Information-Geometric Decomposition in Spike Analysis Hiroyuki Nakahara, Shun-ichi Amari

Information-Geometrical Significance of Sparsity in Gallager Codes Toshiyuki Tanaka, Shiro Ikeda, Shun-ichi Amari

Intransitive Likelihood-Ratio Classifiers Jeff Bilmes, Gang Ji, Marina Meila

Iterative Double Clustering for Unsupervised and Semi-Supervised Learning Ran El-Yaniv, Oren Souroujon

K-Local Hyperplane and Convex Distance Nearest Neighbor Algorithms Pascal Vincent, Yoshua Bengio

Kernel Feature Spaces and Nonlinear Blind Souce Separation Stefan Harmeling, Andreas Ziehe, Motoaki Kawanabe, Klaus-Robert Müller

Kernel Logistic Regression and the Import Vector Machine Ji Zhu, Trevor Hastie

Kernel Machines and Boolean Functions Adam Kowalczyk, Alex J. Smola, Robert C. Williamson

KLD-Sampling: Adaptive Particle Filters Dieter Fox

Laplacian Eigenmaps and Spectral Techniques for Embedding and Clustering Mikhail Belkin, Partha Niyogi

Latent Dirichlet Allocation David M. Blei, Andrew Y. Ng, Michael I. Jordan

Learning a Gaussian Process Prior for Automatically Generating Music Playlists John C. Platt, Christopher J. C. Burges, Steven Swenson, Christopher Weare, Alice Zheng

Learning Body Pose via Specialized Maps Rómer Rosales, Stan Sclaroff

Learning Discriminative Feature Transforms to Low Dimensions in Low Dimentions Kari Torkkola

Learning from Infinite Data in Finite Time Pedro Domingos, Geoff Hulten

Learning Hierarchical Structures with Linear Relational Embedding Alberto Paccanaro, Geoffrey E. Hinton

Learning Lateral Interactions for Feature Binding and Sensory Segmentation Heiko Wersing

Learning Spike-Based Correlations and Conditional Probabilities in Silicon Aaron P. Shon, David Hsu, Chris Diorio

Linear-Time Inference in Hierarchical HMMs Kevin P. Murphy, Mark A. Paskin

Linking Motor Learning to Function Approximation: Learning in an Unlearnable Force Field O. Donchin, Reza Shadmehr

Matching Free Trees with Replicator Equations Marcello Pelillo

Means, Correlations and Bounds Martijn Leisink, Bert Kappen

MIME: Mutual Information Minimization and Entropy Maximization for Bayesian Belief Propagation Anand Rangarajan, Alan L. Yuille

Minimax Probability Machine Gert Lanckriet, Laurent E. Ghaoui, Chiranjib Bhattacharyya, Michael I. Jordan

Model Based Population Tracking and Automatic Detection of Distribution Changes Igor V. Cadez, P. S. Bradley

Model-Free Least-Squares Policy Iteration Michail G. Lagoudakis, Ronald Parr

Modeling Temporal Structure in Classical Conditioning Aaron C. Courville, David S. Touretzky

Modeling the Modulatory Effect of Attention on Human Spatial Vision Laurent Itti, Jochen Braun, Christof Koch

Modularity in the Motor System: Decomposition of Muscle Patterns as Combinations of Time-Varying Synergies A. D'avella, M. C. Tresch

Motivated Reinforcement Learning Peter Dayan

Multi Dimensional ICA to Separate Correlated Sources Roland Vollgraf, Klaus Obermayer

Multiagent Planning with Factored MDPs Carlos Guestrin, Daphne Koller, Ronald Parr

Multiplicative Updates for Classification by Mixture Models Lawrence K. Saul, Daniel D. Lee

Natural Language Grammar Induction Using a Constituent-Context Model Dan Klein, Christopher D. Manning

Neural Implementation of Bayesian Inference in Population Codes Si Wu, Shun-ichi Amari

Novel Iteration Schemes for the Cluster Variation Method Hilbert J. Kappen, Wim Wiegerinck

On Discriminative vs. Generative Classifiers: A Comparison of Logistic Regression and Naive Bayes Andrew Y. Ng, Michael I. Jordan

On Kernel-Target Alignment Nello Cristianini, John Shawe-Taylor, André Elisseeff, Jaz S. Kandola

On Spectral Clustering: Analysis and an Algorithm Andrew Y. Ng, Michael I. Jordan, Yair Weiss

On the Concentration of Spectral Properties John Shawe-Taylor, Nello Cristianini, Jaz S. Kandola

On the Convergence of Leveraging Gunnar Rätsch, Sebastian Mika, Manfred K. Warmuth

On the Generalization Ability of On-Line Learning Algorithms Nicolò Cesa-bianchi, Alex Conconi, Claudio Gentile

Online Learning with Kernels Jyrki Kivinen, Alex J. Smola, Robert C. Williamson

Optimising Synchronisation Times for Mobile Devices Neil D. Lawrence, Antony I. T. Rowstron, Christopher M. Bishop, Michael J. Taylor

Orientation-Selective aVLSI Spiking Neurons Shih-Chii Liu, Jörg Kramer, Giacomo Indiveri, Tobi Delbrück, Rodney J. Douglas

Orientational and Geometric Determinants of Place and Head-Direction Neil Burgess, Tom Hartley

PAC Generalization Bounds for Co-Training Sanjoy Dasgupta, Michael L. Littman, David A. McAllester

Partially Labeled Classification with Markov Random Walks Martin Szummer, Tommi Jaakkola

Perceptual Metamers in Stereoscopic Vision B. T. Backus

Playing Is Believing: The Role of Beliefs in Multi-Agent Learning Yu-Han Chang, Leslie Pack Kaelbling

Pranking with Ranking Koby Crammer, Yoram Singer

Predictive Representations of State Michael L. Littman, Richard S. Sutton

Probabilistic Abstraction Hierarchies Eran Segal, Daphne Koller, Dirk Ormoneit

Probabilistic Inference of Hand Motion from Neural Activity in Motor Cortex Yun Gao, Michael J. Black, Elie Bienenstock, Shy Shoham, John P. Donoghue

Probabilistic Principles in Unsupervised Learning of Visual Structure: Human Data and a Model Shimon Edelman, Benjamin P. Hiles, Hwajin Yang, Nathan Intrator

Prodding the ROC Curve: Constrained Optimization of Classifier Performance Michael Mozer, Robert Dodier, Michael D. Colagrosso, Cesar Guerra-Salcedo, Richard Wolniewicz

Product Analysis: Learning to Model Observations as Products of Hidden Variables Brendan J. Frey, Anitha Kannan, Nebojsa Jojic

Products of Gaussians Christopher Williams, Felix V. Agakov, Stephen N. Felderhof

Quantizing Density Estimators Peter Meinicke, Helge Ritter

Rao-Blackwellised Particle Filtering via Data Augmentation Christophe Andrieu, Nando D. Freitas, Arnaud Doucet

Rates of Convergence of Performance Gradient Estimates Using Function Approximation and Bias in Reinforcement Learning Gregory Z. Grudic, Lyle H. Ungar

Receptive Field Structure of Flow Detectors for Heading Perception J. A. Beintema, M. Lappe, Alexander C. Berg

Reducing Multiclass to Binary by Coupling Probability Estimates B. Zadrozny

Reinforcement Learning and Time Perception -- a Model of Animal Experiments Jonathan L. Shapiro, J. Wearden

Reinforcement Learning with Long Short-Term Memory Bram Bakker

Relative Density Nets: A New Way to Combine Backpropagation with HMM's Andrew D. Brown, Geoffrey E. Hinton

Risk Sensitive Particle Filters Sebastian Thrun, John Langford, Vandi Verma

Sampling Techniques for Kernel Methods Dimitris Achlioptas, Frank Mcsherry, Bernhard Schölkopf

Scaling Laws and Local Minima in Hebbian ICA Magnus Rattray, Gleb Basalyga

Self-Regulation Mechanism of Temporally Asymmetric Hebbian Plasticity N. Matsumoto, M. Okada

Semi-Supervised MarginBoost Florence d'Alché-Buc, Yves Grandvalet, Christophe Ambroise

Sequential Noise Compensation by Sequential Monte Carlo Method K. Yao, S. Nakamura

Small-World Phenomena and the Dynamics of Information Jon M. Kleinberg

Spectral Kernel Methods for Clustering Nello Cristianini, John Shawe-Taylor, Jaz S. Kandola

Spectral Relaxation for K-Means Clustering Hongyuan Zha, Xiaofeng He, Chris Ding, Ming Gu, Horst D. Simon

Speech Recognition Using SVMs N. Smith, Mark Gales

Speech Recognition with Missing Data Using Recurrent Neural Nets S. Parveen, P. Green

Spike Timing and the Coding of Naturalistic Sounds in a Central Auditory Area of Songbirds B. D. Wright, Kamal Sen, William Bialek, A. J. Doupe

Stabilizing Value Function Approximation with the BFBP Algorithm Xin Wang, Thomas G. Dietterich

Stochastic Mixed-Signal VLSI Architecture for High-Dimensional Kernel Machines Roman Genov, Gert Cauwenberghs

Switch Packet Arbitration via Queue-Learning Timothy X. Brown

TAP Gibbs Free Energy, Belief Propagation and Sparsity Lehel Csató, Manfred Opper, Ole Winther

Tempo Tracking and Rhythm Quantization by Sequential Monte Carlo Ali Taylan Cemgil, Bert Kappen

The Concave-Convex Procedure (CCCP) Alan L. Yuille, Anand Rangarajan

The Emergence of Multiple Movement Units in the Presence of Noise and Feedback Delay Michael Kositsky, Andrew G. Barto

The Fidelity of Local Ordinal Encoding Javid Sadr, Sayan Mukherjee, Keith Thoresz, Pawan Sinha

The G Factor: Relating Distributions on Features to Distributions on Images James M. Coughlan, Alan L. Yuille

The Infinite Hidden Markov Model Matthew J. Beal, Zoubin Ghahramani, Carl E. Rasmussen

The Intelligent Surfer: Probabilistic Combination of Link and Content Information in PageRank Matthew Richardson, Pedro Domingos

The Method of Quantum Clustering David Horn, Assaf Gottlieb

The Noisy Euclidean Traveling Salesman Problem and Learning Mikio L. Braun, Joachim M. Buhmann

The Steering Approach for Multi-Criteria Reinforcement Learning Shie Mannor, Nahum Shimkin

The Unified Propagation and Scaling Algorithm Yee W. Teh, Max Welling

Thin Junction Trees Francis R. Bach, Michael I. Jordan

Transform-Invariant Image Decomposition with Similarity Templates Chris Stauffer, Erik Miller, Kinh Tieu

Tree-Based Reparameterization for Approximate Inference on Loopy Graphs Martin J. Wainwright, Tommi Jaakkola, Alan S. Willsky

Unsupervised Learning of Human Motion Models Yang Song, Luis Goncalves, Pietro Perona

Using Vocabulary Knowledge in Bayesian Multinomial Estimation Thomas L. Griffiths, Joshua B. Tenenbaum

Variance Reduction Techniques for Gradient Estimates in Reinforcement Learning Evan Greensmith, Peter L. Bartlett, Jonathan Baxter

Very Loopy Belief Propagation for Unwrapping Phase Images Brendan J. Frey, Ralf Koetter, Nemanja Petrovic

Why Neuronal Dynamics Should Control Synaptic Learning Rules Jesper Tegnér, Ádám Kepecs