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

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