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