NIPS*2001 The Program
	Over 650 technical papers have been submitted for the 2001 Conference. Each was carefully reviewed by three referees. Twenty-five papers were accepted for oral presentation, and 171 papers were accepted for poster presentation. All accepted papers will appear in the Proceedings, which will be available online, on CD-ROM, and as a book from MIT Press. The CD-ROM version will be distributed to everyone who registers for the Conference. The MIT Press book must be ordered separately on the registration form on page 9 of the brochure.
	Oral Presentations Contact Author Authors Title Bilmes Jeff Bilmes, Gang Ji, Marina Meila Intransitive Likelihood ratio classifiers Crammer Koby Crammer, Yoram Singer Pranking with Ranking Dayan Peter Dayan and Angela Yu ACh, Uncertainty, and Cortical Inference de Farias Daniela Pucci de Farias, Benjamin Van Roy Approximate Dynamic Programming via Linear Programming Greensmith Evan Greensmith, Peter L. Bartlett, Jonathan Baxter Variance Reduction Techniques for Gradient Estimates in Reinforcement Learning Guestrin Carlos Guestrin, Daphne Koller and Ronald Parr Multiagent Planning with Factored MDPs Ikeda Shiro Ikeda, Toshiyuki Tanaka, and Shun-ichi Amari Information Geometrical Framework for Analyzing Belief Propagation Decoder Manning Dan Klein and Christopher D. Manning Natural Language Grammar Induction using a Constituent-Context Model McSherry Dimitris Achlioptas, Frank McSherry, and Bernhard Scholkopf Sampling Techniques for Kernel Methods Ng Andrew Y. Ng, Michael I. Jordan, and Yair Weiss On Spectral Clustering: Analysis and an algorithm Raphael Christopher Raphael A Musical Turing Test Rasmussen Carl Edward Rasmussen, Zoubin Ghahramani Infinite Mixtures of Gaussian Process Experts Rokers David Jacobs, Bas Rokers and Archisman Rudra Fragment completion in humans and machines Roweis Sam T. Roweis, Lawrence K. Saul, Geoffrey E. Hinton Global Coordination of Local Linear Models Schwartz Odelia Schwartz, E. J. Chichilnisky, Eero P. Simoncelli Characterizing neural gain control using spike-triggered covariance Shamir Maoz Shamir Haim Sompolinsky Correlation Codes in Neuronal Populations Shon Aaron P. Shon, David W. Hsu, Chris Diorio Learning spike-based correlations and conditional probabilities in silicon Sollich Peter Sollich Gaussian Process Regression with Mismatched Models Thrun Sebastian Thrun, John Langford, Vandi Verma Risk Sensitive Particle Filters Torralba Antonio Torralba and Pawan Sinha Contextual Modulation of Target Saliency Viola Paul Viola and Michael Jones Fast and Robust Classification using Asymmetric AdaBoost and a Detector Cascade Wainwright Martin Wainwright, Tommi Jaakkola and Alan Willsky Tree-based reparameterization for approximate estimation on loopy graphs Warmuth Manfred K. Warmuth, Gunnar Raetsch, Michael Mathieson, Jun Liao, Christian Lemmen Active Learning in the Drug Discovery Process Williams Lance Williams and John Zweck A Rotation and Translation Invariant Discrete Saliency Network Yuille Alan L. Yuille and Anand Rangarajan The Concave-Convex Principle (CCCP)
	Spotlight Presentations Contact Author Authors Title Beal Matthew J. Beal and Zoubin Ghahramani and Carl E. Rasmussen The Infinite Hidden Markov Model Beintema Jaap A. Beintema, Albert V. van den Berg, Markus Lappe Receptive field structure of flow detectors for heading perception Bengio Ronan Collobert and Samy Bengio and Yoshua Bengio A Parallel Mixture of SVMs for Very Large Scale Problems Bhattacharyya Gert R. G. Lanckriet, Laurent El Ghaoui, Chiranjib Bhattacharyya, Michael I. Jordan Minimax Probability Machine Brown Timothy X Brown Switch Packet Arbitration via Queue Learning Brown Andrew D. Brown and Geoffrey E. Hinton Relative Density Nets: A New Way to Combine Backpropagation with HMM's chapelle Olivier Chapelle, Bernhard Scholkopf Incorporating Invariances in Nonlinear Support Vector Machines Chechik Gal Chechik, Amir Globerson, Tali Tishby, Michael J. Anderson, Eric D. Young and Israel Nelken Group redundancy measures reveal redundancy reduction in the auditory pathway Coughlan James M. Coughlan and Alan L. Yuille The g Factor: Relating Distributions on Features to Distributions on Images Cristianini Nello Cristianini, John Shawe-Taylor, Andre Elisseeff, Jaz Kandola On Kernel-Target Alignment Dasgupta Sanjoy Dasgupta, Michael Littman, and David McAllester PAC Generalization Bounds for Co-training Dietterich Thomas G. Dietterich and Xin Wang Batch Value Function Approximation via Support Vectors Franklin Judy A. Franklin Improvisation and Learning Frey Brendan J. Frey, Nebojsa Jojic Fast, large-scale transformation-invariant clustering Genov Roman Genov and Gert Cauwenberghs Stochastic Mixed-Signal VLSI Architecture for High-Dimensional Kernel Machines Haffner Patrick Haffner Escaping the Convex Hull with Extrapolated Vector Machines Hahnloser Richard H.R. Hahnloser, Xiaohui Xie, H. Sebastian Seung A theory of integration in the head-direction system Harmeling Stefan Harmeling, Andreas Ziehe, Motoaki Kawanabe, Klaus-Robert Mueller Kernel Feature Spaces and Nonlinear Blind Source Separation Herbrich Ralf Herbrich, Robert C. Williamson Algorithmic Luckiness Hutter Marcus Hutter Distribution of Mutual Information Kakade Sham Kakade A Natural Policy Gradient Kepecs Adam Kepecs and Srdihar Raghavachari 3 state neurons for contextual processing Koenig S. Koenig and M. Likhachev Incremental A* Kositsky Michael Kositsky and Andrew G. Barto The Emergence of Multiple Movement Units in the Presence of Noise and Feedback Delay Littman Michael L. Littman, Richard S. Sutton, Satinder Singh Predictive Representations of State Liu Shih-Chii Liu, Jorg Kramer, Giacomo Indiveri, Tobias Delbruck, and Rodney Douglas Orientation-Selective aVLSI Spiking Neurons Nemenman Ilya Nemenman, Fariel Shafee, and William Bialek Entropy and Inference, Revisited O'Reilly Randall C. O'Reilly and Richard S. Busby Generalizable Relational Binding from Coarse-coded Distributed Representations Parr Michail G. Lagoudakis and Ronald Parr Model-Free Least Squares Policy Iteration Platt John C. Platt, Christopher J. C. Burges, Steven Swenson, Christopher Weare, Alice Zheng Learning a Gaussian Process Prior for Automatically Generating Music Playlists Ratsch Gunnar Ratsch, Sebastian Mika, Manfred K. Warmuth On the Convergence of Leveraging Rattray Magnus Rattray and Gleb Basalyga Scaling laws and local minima in Hebbian ICA Rehder Bob Rehder Causal categorization with Bayes' nets Samsonovich Giorgio A. Ascoli and Alexei Samsonovich Bayesian morphometry of hippocampal cells suggests same-cell somatodendritic repulsion Serre Bernd Heisele, Thomas Serre, Massimiliano Pontil, Thomas Vetter and Tomaso Poggio Categorization by Learning and Combining Object Parts Smith Nathan D. Smith and Mark J.F. Gales Speech Recognition using SVMs Smola Jyrki Kivinen and Alexander J. Smola and Robert C. Williamson Online Learning with Kernels Szummer Martin Szummer and Tommi Jaakkola Clustering and efficient use of unlabeled examples Teh Yee Whye Teh and Max Welling The Unified Propagation and Scaling Algorithm Tipping Anita C Faul and Michael E Tipping Analysis of Sparse Bayesian Learning Wu Si Wu and Shun-ichi Amari Neural Implementation of Bayesian Inference in Population Codes Zimmermann Hans-Georg Zimmermann, Ralph Neuneier, Ralph Grothmann Active Portfolio-Management based on Error Correction Neural Networks
	Poster Presentations Contact Author Authors Title Munos Remi Munos Efficient Resource Allocation for Markov Decision Processes Mansour Eyal Even-Dar and Yishay Mansour Convergence of Optimistic and Incremental Q-learning Bakker Bram Bakker Reinforcement Learning with Long Short-Term Memory Mannor Shie Mannor and Nahum Shimkin The Steering Approach for Multi-Criteria Reinforcement Learning Dietterich Xin Wang and Thomas G. Dietterich Stabilizing Value Function Approximation with the BFBP Algorithm Grudic Gregory Z. Grudic and Lyle H. Ungar Rates of Convergence of Performance Gradient Estimates Using Function Approximation and Bias in Reinforcement Learning Schuurmans Dale Schuurmans and Relu Patrascu Direct value-approximation for factored MDPs Chang Yu-Han Chang and Leslie Pack Kaelbling Playing is believing: The role of beliefs in multi-agent learning Zha Hongyuan Zha , Xiaofeng He,Chris Ding,Horst Simon,Ming Gu Spectral Relaxation for K-means Clustering Niyogi Mikhail Belkin, Partha Niyogi Laplacian Eigenmaps and Spectral Techniques for Embedding and Clustering Figueiredo Mario A. T. Figueiredo Adaptive Sparseness Using Jeffreys Prior Horn David Horn and Assaf Gottlieb The Method of Quantum Clustering Kisilev Pavel Kisilev, Michael Zibulevsky, Yehoshua Y. Zeevi, Barak Pearlmutter Blind Source Separation via Multinode Sparse Representation Kohlmorgen Jens Kohlmorgen, Steven Lemm A Dynamic HMM for On-line Segmentation of Sequential Data Goldman Qi Zhang and Sally A. Goldman EM-DD: An Improved Multiple-Instance Learning Technique Golland Polina Golland Discriminative Direction for Kernel Classifiers Zhang Tong Zhang A General Greedy Approximation Algorithm with Applications Zhu Ji Zhu, Trevor Hastie Kernel Logistic Regression and the Import Vector Machine Wersing Heiko Wersing Learning Lateral Interactions for Feature Binding and Sensory Segmentation Williams C. K. I. Williams and Felix V. Agakov and Stephen. N. Felderhof Products of Gaussians Cristianini Nello Cristianini, John Shawe-Taylor, Jaz Kandola Spectral Kernel Methods for Clustering Pelillo Marcello Pelillo Matching free trees with replicator equations d'Alché-Buc F. d'Alché-Buc, Y. Grandvalet and C. Ambroise Semi-Supervised MarginBoost Sykacek Peter Sykacek and Stephen Roberts Bayesian time series classification Vollgraf Roland Vollgraf and Klaus Obermayer Multi Dimensional ICA to Separate Correlated Sources Shimodaira Hiroshi Shimodaira, Ken-ichi Noma, Mitsuru Nakai, Shigeki Sagayama Dynamic Time-Alignment Kernel in Support Vector Machine Seeger Matthias Seeger Covariance Kernels from Bayesian Generative Models Segal Eran Segal, Daphne Koller, Dirk Ormoneit Probabilistic Abstraction Hierarchies Slonim Noam Slonim, Nir Friedman and Naftali Tishby Agglomerative Multivariate Information Bottleneck Frey Brendan J. Frey, Ralf Koetter, Nemanja Petrovic Very loopy belief propagation for unwrapping phase images El-Yaniv Ran El-Yaniv and Oren Souroujon Iterative Double Clustering for Semi and Unsupervised Learning Domeniconi Carlotta Domeniconi, Dimitrios Gunopulos Adaptive Nearest Neighbor Classification using Support Vector Machines Yuille Anand Rangarajan and Alan L. Yuille MIME: Mutual Information Minimization and Entropy Maximization for Bayesian Belief Propagation Elisseeff Andre Elisseeff and Jason Weston A kernel method for multi-labelled classification Bennett Jinbo Bi and Kristin P. Bennett Duality, Geometry, and Support Vector Regression Dasgupta Michael Collins, Sanjoy Dasgupta, and Robert E. Schapire A Generalization of Principal Component Analysis to the Exponential Family Paccanaro Alberto Paccanaro, Geoffrey E. Hinton Learning hierarchical structures with Linear Relational Embedding Fine Shai Fine, Katya Scheinberg Incremental Learning and Selective Sampling via Parametric Optimization Framework for SVM Meinicke Peter Meinicke, Helge Ritter Quantizing Density Estimators Bach Francis R. Bach, Michael I. Jordan Thin Junction Trees Jaakkola Tommi Jaakkola and Hava Siegelmann Active Information Retrieval Saul Lawrence K. Saul and Daniel D. Lee Discriminative Mixture Modeling Blei David M. Blei, Andrew Y. Ng, Michael I. Jordan Latent Dirichlet Allocation Langford John Langford and Rich Caruana (Not) Bounding the True Error Torkkola Kari Torkkola Learning Discriminative Feature Transforms to Low Dimensions in Low Dimensions Ng Andrew Y. Ng and Michael I. Jordan On Discriminative vs. Generative classifiers: A comparison of logistic regression and naive Bayes Tsuda Koji Tsuda, Motoaki Kawanabe, Gunnar Raetsch, Soeren Sonnenburg, Klaus-Robert Mueller A New Discriminative Kernel from Probabilistic Models Domingos Pedro Domingos, Geoff Hulten Learning from Infinite Data in Finite Time Duffy Michael Collins and Nigel Duffy Convolution Kernels for Natural Language Littman Michael L. Littman and Michael Kearns and Satinder Singh An Efficient Exact Algorithm for Singly Connected Graphical Games Winther Lehel Csat\'o, Manfred Opper and Ole Winther TAP Gibbs Free Energy, Belief Propagation and Sparsity de Freitas Christophe Andrieu, Nando de Freitas and Arnaud Doucet Rao-Blackwellised particle filtering via data augmentation Vincent Pascal Vincent and Yoshua Bengio K-Local Hyperplane and Convex Distance Nearest Neighbour Algorithms Fox Dieter Fox KLD-Sampling: Adaptive Particle Filters and Mobile Robot Localization Frey Brendan J. Frey, Anitha Kannan, Nebojsa Jojic Product Analysis: Learning to model observations as products of hidden variables Zadrozny Bianca Zadrozny Reducing multiclass to binary by coupling probability estimates Malzahn Dorthe Malzahn and Manfred Opper A replica variational approach to learning curves Song Yang Song, Luis Goncalves, and Pietro Perona Learning structure for human motion Murphy Kevin P. Murphy and Mark A. Paskin Linear-time Inference in Hierarchical HMMs Lawrence Neil D Lawrence Antony I.T. Rowstron Christopher M. Bishop Michael J. Taylor Optimising Synchronisation Times for Mobile Devices Smyth Igor V. Cadez and Padhraic Smyth Bayesian predictive profiles with applications to retail transaction data Ontrup Jörg Ontrup and Helge Ritter Hyperbolic Self-Organizing Maps for Semantic Navigation Cadez Igor V. Cadez and Paul S. Bradley Model Based Population Tracking and Automatic Detection of Distribution Changes Yang Ming-Hsuan Yang Face Recognition Using Kernel Methods Griffiths Thomas L. Griffiths and Joshua B. Tenenbaum Exploiting weak prior knowledge in Bayesian parameter estimation Mozer Michael C. Mozer, Robert Dodier, Michael D. Colagrosso, Cesar Guerra-Salcedo, Richard Wolniewicz Prodding the ROC Curve: Constrained Optimization of Classifier Performance Bengio Nicolas Chapados, Yoshua Bengio, Pascal Vincent, Joumana Ghosn, Charles Dugas, Ichiro Takeuchi, Linyan Meng High-Dimensional Data Inference for Car Insurance Premia Estimation Isbell Charles Lee Isbell Jr. / Christian R. Shelton / Michael Kearns / Satinder Singh / Peter Stone Cobot: A Social Reinforcement Learning Agent Richardson Matt Richardson and Pedro Domingos The Intelligent Surfer: Probabilistic Combination of Link and Content Information in PageRank Kappen Ali Taylan Cemgil and Bert Kappen Tempo tracking and rhythm quantisation by sequential Monte Carlo Roth Roni Khardon, Dan Roth, Rocco Servedio Efficiency versus Convergence of Boolean Kernels for On-Line Learning Algorithms Park Shun-ichi Amari, Hyeyoung Park, Tomoko Ozeki Geometrical Singularities in the Neuromanifold of Multilayer Perceptrons Zhang Tong Zhang Generalization Performance of Some Learning Problems in Hilbert Functional Spaces Leisink Martijn A.R. Leisink and Hilbert J. Kappen Means, Correlations and Bounds Tanaka Toshiyuki Tanaka, Shiro Ikeda, Shun-ichi Amari Information-Geometrical Significance of Sparsity in Gallager Codes Conconi Nicolo' Cesa-Bianchi, Alex Conconi, Claudio Gentile On the generalization ability of on-line learning algorithms Wong K. Y. Michael Wong and Fuli Li Fast parameter estimation using Green's functions Lebanon Guy Lebanon and John Lafferty Boosting and Maximum Likelihood for Exponential Models Schmitt Michael Schmitt Computing time lower bounds for recurrent sigmoidal neural networks Kappen Hilbert J. Kappen A novel iteration scheme for the Cluster Variation Method Braun Mikio L. Braun, Joachim M. Buhmann The Noisy Euclidian Traveling Salesman Problem and Learning Shawe-Taylor John Shawe-Taylor, Nello Cristianini, Jaz Kandola On the Concentration of Spectral Properties Opper Manfred Opper and Robert Urbanczik Asymptotic Universality for Learning Curves of Support Vector Machines Smola Adam Kowalczyk and Alexander J. Smola and Robert C. Williamson Kernel Machines and Boolean Functions Dayan Peter Dayan Motivated Reinforcement Learning Yarlett Daniel G. Yarlett and Michael J.A. Ramscar A Quantitative Model of Counterfactual Reasoning Edelman Shimon Edelman, Hwajin Yang, Benjamin P. Hiles, Nathan Intrator Probabilistic principles in unsupervised learning of visual structure: human data and a model O'Reilly Randall C. O'Reilly and Rodolfo Soto A Model of the Phonological Loop: Generalization and Binding Ruml Wheeler Ruml Constructing Distributed Representations Using Additive Clustering Paskin Mark A. Paskin Grammatical Bigrams Mozer Michael C. Mozer, Michael D. Colagrosso, David E. Huber A Rational Analysis of Cognitive Control in a Speeded Discrimination Task Courville Aaron C. Courville and David S. Touretzky Modeling Temporal Structure in Classical Conditioning Negishi Michiro Negishi, Stephen Jose Hanson Grammar Transfer in a Second Order Recurrent Neural Network Shapiro J. L Shapiro and John Wearden Reinforcement Learning and Time Perception - a Model of Animal Experiments Narayanan Srini Narayanan and Daniel Jurafsky A Bayesian Model Predicts Human Parse Preference and Reading Times in Sentence Processing Black Yun Gao, Michael J. Black, Elie Bienenstock, John Donoghue Probabilistic Inference of Hand Motion from Neural Activity in Motor Cortex Trappenberg Thomas P. Trappenberg, Edmund T. Rolls, Simon M. Stringer Effective size of receptive fields of inferior temporal visual cortex neurons in natural scenes Nakahara Hiroyuki Nakahara, Shun-ichi Amari Information-geometric decomposition in spike analysis Xie Xiaohui Xie and Martin Giese Nonlinear dynamics of direction-selective recurrent neural media Colonius Hans Colonius, Adele Diederich A maximum-likelihood approach to modeling multisensory enhancement Burgess Neil Burgess, Tom Hartley Orientational and geometric determinants of place and head-direction Blankertz Benjamin Blankertz and Gabriel Curio and Klaus-Robert Mueller Classifying Single Trial EEG: Towards Brain Computer Interfacing Baeuml Julian Eggert and Berthold Baeuml Exact differential equation population dynamics for Integrate-and-Fire neurons Rucci Michele Rucci and Antonino Casile Eye movements and the maturation of cortical orientation selectivity Wenning Gregor Wenning and Klaus Obermayer Activity Driven Adaptive Stochastic Resonance Latham Peter E. Latham Associative memory in realistic neuronal networks Sadr Javid Sadr, Sayan Mukherjee, Keith Thoresz, Pawan Sinha The Fidelity of Local Ordinal Encoding d'Avella Andrea d'Avella and Matthew C. Tresch Modularity in the motor system: decomposition of muscle patterns as combinations of time-varying synergies Donchin Opher Donchin; Reza Shadmehr Linking motor learning to function approximation: learning in an unlearnable force field tegner Jesper Tegner, Adam Kepecs Why neuronal dynamics should control synaptic learning rules Matsumoto Narihisa Matsumoto and Masato Okada Self-regulation mechanism of Temporally Asymmetric Hebbian plasticity Wright Brian D. Wright, Kamal Sen, William Bialek and Allison J. Doupe Spike timing and the coding of naturalistic sounds in a central auditory area of song birds Morie Takashi Morie, Tomohiro Matsuura, Makoto Nagata, and Atsushi Iwata An Efficient Clustering Algorithm Using Stochastic Association Model and Its Implementation Using Nanostructures Bofill Adria Bofill; Alan F. Murray Working Circuits for VLSI Implementation of Temporally Asymmetric Hebbian Learning Shibata Toshihiko YAMASAKI and Tadashi SHIBATA An Analog Soft-Pattern-Matching Classifier and Its Application to Overlapping Pattern Separation Campbell William M. Campbell A Sequence Kernel and its Application to Speaker Recognition Wrigley Stuart N. Wrigley and Guy J. Brown A Neural Oscillator Model of Auditory Selective Attention Parveen Shahla Parveen, Phil Green Speech Recognition with Missing Data using Recurrent Neural Nets Frey Brendan J. Frey, Trausti T. Kristjansson, Li Deng, Alex Acero Learning dynamic noise models from noisy speech for robust speech recognition Mueller Frank Meinecke, Andreas Ziehe, Motoaki Kawanabe, Klaus-Robert Mueller Estimating the Reliability of ICA Projections hershey John Hershey and Michael Casey Audio-Visual Speech Separation Using Hidden Markov Models Yao Kaisheng Yao and Satoshi Nakamura Sequential noise compensation by sequential Monte Carlo method Solari Silvio P. Sabatini, Fabio Solari, Giulia Andreani, Chiara Bartolozzi, and Giacomo M. Bisio A hierarchical model of complex cells in visual cortex for the binocular perception of motion in depth Backus Benjamin T. Backus Perceptual Metamers in Stereoscopic Vision Stauffer Chris Stauffer, Erik Miller, Kinh Tieu Transform-invariant image decomposition with similarity templates Itti Laurent Itti Modeling the Modulatory Effect of Attention on Human Spatial Vision Yu Stella X. Yu and Jianbo Shi Grouping with Bias Rosales Romer Rosales and Stan Sclaroff Learning Body Pose via Specialized Maps Perona Pietro Perona and Marzia Polito Grouping and dimensionality reduction by locally linear embedding
	We have attempted to ensure that all information is correct, but we cannot guarantee it. Please send website-related comments and corrections to: (for webpage content-related issues) Alexander Gray, Carnegie Mellon University, agray+nips@cs.cmu.edu, or (for server-related or script-related issues) Xin Wang, Oregon State University, wangxi@cs.orst.edu.