NIPS 2001 Proceedings

Advances in Neural Information Processing Systems 14 (NIPS 2001)

The papers below appear in Advances in Neural Information Processing Systems 14 edited by T.G. Dietterich and S. Becker and Z. Ghahramani.
They are proceedings from the conference, "Neural Information Processing Systems 2001."

Modeling Temporal Structure in Classical Conditioning Aaron C. Courville, David S. Touretzky
Motivated Reinforcement Learning Peter Dayan
Probabilistic principles in unsupervised learning of visual structure: human data and a model Shimon Edelman, Benjamin P. Hiles, Hwajin Yang, Nathan Intrator
Fragment Completion in Humans and Machines David Jacobs, Bas Rokers, Archisman Rudra, Zili Liu
Natural Language Grammar Induction Using a Constituent-Context Model Dan Klein, Christopher D. Manning
The Emergence of Multiple Movement Units in the Presence of Noise and Feedback Delay Michael Kositsky, Andrew G. Barto
A Rational Analysis of Cognitive Control in a Speeded Discrimination Task Michael C. Mozer, Michael D. Colagrosso, David E. Huber
A Bayesian Model Predicts Human Parse Preference and Reading Times in Sentence Processing S. Narayanan, Daniel Jurafsky
Grammar Transfer in a Second Order Recurrent Neural Network Michiro Negishi, Stephen J. Hanson
Generalizable Relational Binding from Coarse-coded Distributed Representations Randall C. O'Reilly, R. S. Busby
A Model of the Phonological Loop: Generalization and Binding Randall C. O'Reilly, R. Soto
Grammatical Bigrams Mark A. Paskin
Causal Categorization with Bayes Nets Bob Rehder
Constructing Distributed Representations Using Additive Clustering Wheeler Ruml
Reinforcement Learning and Time Perception -- a Model of Animal Experiments Jonathan L. Shapiro, J. Wearden
A Quantitative Model of Counterfactual Reasoning Daniel Yarlett, Michael Ramscar
Bayesian morphometry of hippocampal cells suggests same-cell somatodendritic repulsion Giorgio A. Ascoli, Alexei V. Samsonovich
Modularity in the motor system: decomposition of muscle patterns as combinations of time-varying synergies A. D'avella, M. C. Tresch
Receptive field structure of flow detectors for heading perception J. A. Beintema, M. Lappe, Alexander C. Berg
Classifying Single Trial EEG: Towards Brain Computer Interfacing Benjamin Blankertz, Gabriel Curio, Klaus-Robert Müller
Orientational and Geometric Determinants of Place and Head-direction Neil Burgess, Tom Hartley
Group Redundancy Measures Reveal Redundancy Reduction in the Auditory Pathway Gal Chechik, Amir Globerson, M. J. Anderson, E. D. Young, Israel Nelken, Naftali Tishby
A Maximum-Likelihood Approach to Modeling Multisensory Enhancement H. Colonius, A. Diederich
ACh, Uncertainty, and Cortical Inference Peter Dayan, Angela J. Yu
Linking Motor Learning to Function Approximation: Learning in an Unlearnable Force Field O. Donchin, Reza Shadmehr
Exact differential equation population dynamics for integrate-and-fire neurons Julian Eggert, Berthold Bäuml
Probabilistic Inference of Hand Motion from Neural Activity in Motor Cortex Yun Gao, Michael J. Black, Elie Bienenstock, Shy Shoham, John P. Donoghue
A theory of neural integration in the head-direction system Richard Hahnloser, Xiaohui Xie, H. S. Seung
3 state neurons for contextual processing Ádám Kepecs, S. Raghavachari
Associative memory in realistic neuronal networks Peter E. Latham
Self-regulation Mechanism of Temporally Asymmetric Hebbian Plasticity N. Matsumoto, M. Okada
Information-Geometric Decomposition in Spike Analysis Hiroyuki Nakahara, Shun-ichi Amari
Eye movements and the maturation of cortical orientation selectivity Antonino Casile, Michele Rucci
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
Why Neuronal Dynamics Should Control Synaptic Learning Rules Jesper Tegnér, Ádám Kepecs
Effective Size of Receptive Fields of Inferior Temporal Visual Cortex Neurons in Natural Scenes Thomas P. Trappenberg, Edmund T. Rolls, Simon M. Stringer
Activity Driven Adaptive Stochastic Resonance Gregor Wenning, Klaus Obermayer
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
Neural Implementation of Bayesian Inference in Population Codes Si Wu, Shun-ichi Amari
Generating velocity tuning by asymmetric recurrent connections Xiaohui Xie, Martin A. Giese
Sampling Techniques for Kernel Methods Dimitris Achlioptas, Frank Mcsherry, Bernhard Schölkopf
Geometrical Singularities in the Neuromanifold of Multilayer Perceptrons Shun-ichi Amari, Hyeyoung Park, Tomoko Ozeki
The Noisy Euclidean Traveling Salesman Problem and Learning Mikio L. Braun, Joachim M. Buhmann
On the Generalization Ability of On-Line Learning Algorithms Nicolò Cesa-bianchi, Alex Conconi, Claudio Gentile
On Kernel-Target Alignment Nello Cristianini, John Shawe-Taylor, André Elisseeff, Jaz S. Kandola
PAC Generalization Bounds for Co-training Sanjoy Dasgupta, Michael L. Littman, David A. McAllester
Analysis of Sparse Bayesian Learning Anita C. Faul, Michael E. Tipping
Algorithmic Luckiness Ralf Herbrich, Robert C. Williamson
Distribution of Mutual Information Marcus Hutter
Information Geometrical Framework for Analyzing Belief Propagation Decoder Shiro Ikeda, Toshiyuki Tanaka, Shun-ichi Amari
Novel iteration schemes for the Cluster Variation Method Hilbert J. Kappen, Wim Wiegerinck
Efficiency versus Convergence of Boolean Kernels for On-Line Learning Algorithms Roni Khardon, Dan Roth, Rocco A. Servedio
Small-World Phenomena and the Dynamics of Information Jon M. Kleinberg
Kernel Machines and Boolean Functions Adam Kowalczyk, Alex J. Smola, Robert C. Williamson
Boosting and Maximum Likelihood for Exponential Models Guy Lebanon, John D. Lafferty
Means, Correlations and Bounds Martijn Leisink, Bert Kappen
A Variational Approach to Learning Curves Dörthe Malzahn, Manfred Opper
Entropy and Inference, Revisited Ilya Nemenman, F. Shafee, William Bialek
Asymptotic Universality for Learning Curves of Support Vector Machines Manfred Opper, Robert Urbanczik
On the Convergence of Leveraging Gunnar Rätsch, Sebastian Mika, Manfred K. K. Warmuth
Scaling Laws and Local Minima in Hebbian ICA Magnus Rattray, Gleb Basalyga
Computing Time Lower Bounds for Recurrent Sigmoidal Neural Networks M. Schmitt
On the Concentration of Spectral Properties John Shawe-Taylor, Nello Cristianini, Jaz S. Kandola
Gaussian Process Regression with Mismatched Models Peter Sollich
Information-Geometrical Significance of Sparsity in Gallager Codes Toshiyuki Tanaka, Shiro Ikeda, Shun-ichi Amari
Fast Parameter Estimation Using Green's Functions K. Wong, F. Li
Generalization Performance of Some Learning Problems in Hilbert Functional Spaces T. Zhang
Semi-supervised MarginBoost Florence D'alché-buc, Yves Grandvalet, Christophe Ambroise
Rao-Blackwellised Particle Filtering via Data Augmentation Christophe Andrieu, Nando D. Freitas, Arnaud Doucet
Thin Junction Trees Francis R. Bach, Michael I. Jordan
The Infinite Hidden Markov Model Matthew J. Beal, Zoubin Ghahramani, Carl E. Rasmussen
Laplacian Eigenmaps and Spectral Techniques for Embedding and Clustering Mikhail Belkin, Partha Niyogi
Duality, Geometry, and Support Vector Regression J. Bi, Kristin P. Bennett
Latent Dirichlet Allocation David M. Blei, Andrew Y. Ng, Michael I. Jordan
Incorporating Invariances in Non-Linear Support Vector Machines Olivier Chapelle, Bernhard Schölkopf
A Generalization of Principal Components Analysis to the Exponential Family Michael Collins, S. Dasgupta, Robert E. Schapire
Convolution Kernels for Natural Language Michael Collins, Nigel Duffy
A Parallel Mixture of SVMs for Very Large Scale Problems Ronan Collobert, Samy Bengio, Yoshua Bengio
Pranking with Ranking Koby Crammer, Yoram Singer
Spectral Kernel Methods for Clustering Nello Cristianini, John Shawe-Taylor, Jaz S. Kandola
TAP Gibbs Free Energy, Belief Propagation and Sparsity Lehel Csató, Manfred Opper, Ole Winther
Adaptive Nearest Neighbor Classification Using Support Vector Machines Carlotta Domeniconi, Dimitrios Gunopulos
Learning from Infinite Data in Finite Time Pedro Domingos, Geoff Hulten
A kernel method for multi-labelled classification André Elisseeff, Jason Weston
Approximate Dynamic Programming via Linear Programming Daniela Farias, Benjamin V. Roy
Adaptive Sparseness Using Jeffreys Prior Mário Figueiredo
Incremental Learning and Selective Sampling via Parametric Optimization Framework for SVM Shai Fine, Katya Scheinberg
KLD-Sampling: Adaptive Particle Filters Dieter Fox
Fast, Large-Scale Transformation-Invariant Clustering Brendan J. Frey, Nebojsa Jojic
Product Analysis: Learning to Model Observations as Products of Hidden Variables Brendan J. Frey, Anitha Kannan, Nebojsa Jojic
Very loopy belief propagation for unwrapping phase images Brendan J. Frey, Ralf Koetter, Nemanja Petrovic
Discriminative Direction for Kernel Classifiers Polina Golland
Escaping the Convex Hull with Extrapolated Vector Machines Patrick Haffner
Kernel Feature Spaces and Nonlinear Blind Souce Separation Stefan Harmeling, Andreas Ziehe, Motoaki Kawanabe, Klaus-Robert Müller
The Method of Quantum Clustering David Horn, Assaf Gottlieb
Active Information Retrieval Tommi Jaakkola, Hava T. Siegelmann
Online Learning with Kernels Jyrki Kivinen, Alex J. Smola, Robert C. Williamson
A Dynamic HMM for On-line Segmentation of Sequential Data Jens Kohlmorgen, Steven Lemm
Minimax Probability Machine Gert Lanckriet, Laurent E. Ghaoui, Chiranjib Bhattacharyya, Michael I. Jordan
(Not) Bounding the True Error John Langford, Rich Caruana
An Efficient, Exact Algorithm for Solving Tree-Structured Graphical Games Michael L. Littman, Michael J. Kearns, Satinder P. Singh
Quantizing Density Estimators Peter Meinicke, Helge Ritter
Linear-time inference in Hierarchical HMMs Kevin P. Murphy, Mark A. Paskin
On Discriminative vs. Generative Classifiers: A comparison of logistic regression and naive Bayes Andrew Y. Ng, Michael I. Jordan
On Spectral Clustering: Analysis and an algorithm Andrew Y. Ng, Michael I. Jordan, Yair Weiss
Learning Hierarchical Structures with Linear Relational Embedding Alberto Paccanaro, Geoffrey E. Hinton
Matching Free Trees with Replicator Equations Marcello Pelillo
MIME: Mutual Information Minimization and Entropy Maximization for Bayesian Belief Propagation Anand Rangarajan, Alan L. Yuille
Infinite Mixtures of Gaussian Process Experts Carl E. Rasmussen, Zoubin Ghahramani
Global Coordination of Local Linear Models Sam T. Roweis, Lawrence K. Saul, Geoffrey E. Hinton
Multiplicative Updates for Classification by Mixture Models Lawrence K. Saul, Daniel D. Lee
Covariance Kernels from Bayesian Generative Models Matthias Seeger
Probabilistic Abstraction Hierarchies Eran Segal, Daphne Koller, Dirk Ormoneit
Dynamic Time-Alignment Kernel in Support Vector Machine Hiroshi Shimodaira, Ken-ichi Noma, Mitsuru Nakai, Shigeki Sagayama
Agglomerative Multivariate Information Bottleneck Noam Slonim, Nir Friedman, Naftali Tishby
Bayesian time series classification Peter Sykacek, Stephen J. Roberts
Partially labeled classification with Markov random walks Martin Szummer, Tommi Jaakkola
The Unified Propagation and Scaling Algorithm Yee W. Teh, Max Welling
Risk Sensitive Particle Filters Sebastian Thrun, John Langford, Vandi Verma
Learning Discriminative Feature Transforms to Low Dimensions in Low Dimentions Kari Torkkola
A New Discriminative Kernel From Probabilistic Models Koji Tsuda, Motoaki Kawanabe, Gunnar Rätsch, Sören Sonnenburg, Klaus-Robert Müller
K-Local Hyperplane and Convex Distance Nearest Neighbor Algorithms Pascal Vincent, Yoshua Bengio
Multi Dimensional ICA to Separate Correlated Sources Roland Vollgraf, Klaus Obermayer
Tree-based reparameterization for approximate inference on loopy graphs Martin J. Wainwright, Tommi Jaakkola, Alan S. Willsky
Learning Lateral Interactions for Feature Binding and Sensory Segmentation Heiko Wersing
Products of Gaussians Christopher Williams, Felix V. Agakov, Stephen N. Felderhof
Iterative Double Clustering for Unsupervised and Semi-Supervised Learning Ran El-Yaniv, Oren Souroujon
The Concave-Convex Procedure (CCCP) Alan L. Yuille, Anand Rangarajan
Reducing multiclass to binary by coupling probability estimates B. Zadrozny
Blind Source Separation via Multinode Sparse Representation Michael Zibulevsky, Pavel Kisilev, Yehoshua Y. Zeevi, Barak A. Pearlmutter
Spectral Relaxation for K-means Clustering Hongyuan Zha, Xiaofeng He, Chris Ding, Ming Gu, Horst D. Simon
A General Greedy Approximation Algorithm with Applications T. Zhang
EM-DD: An Improved Multiple-Instance Learning Technique Qi Zhang, Sally A. Goldman
Kernel Logistic Regression and the Import Vector Machine Ji Zhu, Trevor Hastie
Citcuits for VLSI Implementation of Temporally Asymmetric Hebbian Learning A. Bofill, D. P. Thompson, Alan F. Murray
Stochastic Mixed-Signal VLSI Architecture for High-Dimensional Kernel Machines Roman Genov, Gert Cauwenberghs
Orientation-Selective aVLSI Spiking Neurons Shih-Chii Liu, Jörg Kramer, Giacomo Indiveri, Tobi Delbrück, Rodney J. Douglas
An Efficient Clustering Algorithm Using Stochastic Association Model and Its Implementation Using Nanostructures Takashi Morie, Tomohiro Matsuura, Makoto Nagata, Atsushi Iwata
Learning Spike-Based Correlations and Conditional Probabilities in Silicon Aaron P. Shon, David Hsu, Chris Diorio
Analog Soft-Pattern-Matching Classifier using Floating-Gate MOS Technology Toshihiko Yamasaki, Tadashi Shibata
Intransitive Likelihood-Ratio Classifiers Jeff Bilmes, Gang Ji, Marina Meila
Relative Density Nets: A New Way to Combine Backpropagation with HMM's Andrew D. Brown, Geoffrey E. Hinton
A Sequence Kernel and its Application to Speaker Recognition William M. Campbell
ALGONQUIN - Learning Dynamic Noise Models From Noisy Speech for Robust Speech Recognition Brendan J. Frey, Trausti T. Kristjansson, Li Deng, Alex Acero
Audio-Visual Sound Separation Via Hidden Markov Models John R. Hershey, Michael Casey
Estimating the Reliability of ICA Projections Frank C. Meinecke, Andreas Ziehe, Motoaki Kawanabe, Klaus-Robert Müller
Speech Recognition with Missing Data using Recurrent Neural Nets S. Parveen, P. Green
Speech Recognition using SVMs N. Smith, Mark Gales
Sequential Noise Compensation by Sequential Monte Carlo Method K. Yao, S. Nakamura
A Neural Oscillator Model of Auditory Selective Attention Stuart N. Wrigley, Guy J. Brown
Perceptual Metamers in Stereoscopic Vision B. T. Backus
The g Factor: Relating Distributions on Features to Distributions on Images James M. Coughlan, Alan L. Yuille
Categorization by Learning and Combining Object Parts Bernd Heisele, Thomas Serre, Massimiliano Pontil, Thomas Vetter, Tomaso Poggio
Modeling the Modulatory Effect of Attention on Human Spatial Vision Laurent Itti, Jochen Braun, Christof Koch
Grouping and dimensionality reduction by locally linear embedding Marzia Polito, Pietro Perona
Learning Body Pose via Specialized Maps Rómer Rosales, Stan Sclaroff
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
The Fidelity of Local Ordinal Encoding Javid Sadr, Sayan Mukherjee, Keith Thoresz, Pawan Sinha
Unsupervised Learning of Human Motion Models Yang Song, Luis Goncalves, Pietro Perona
Transform-invariant Image Decomposition with Similarity Templates Chris Stauffer, Erik Miller, Kinh Tieu
Contextual Modulation of Target Saliency Antonio Torralba
Fast and Robust Classification using Asymmetric AdaBoost and a Detector Cascade Paul Viola, Michael Jones
A Rotation and Translation Invariant Discrete Saliency Network Lance R. Williams, John W. Zweck
Grouping with Bias Stella X. Yu, Jianbo Shi
Switch Packet Arbitration via Queue-Learning Timothy X. Brown
Model Based Population Tracking and Automatic Detection of Distribution Changes Igor V. Cadez, P. S. Bradley
Bayesian Predictive Profiles With Applications to Retail Transaction Data Igor V. Cadez, Padhraic Smyth
Tempo tracking and rhythm quantization by sequential Monte Carlo Ali Taylan Cemgil, Bert Kappen
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
Improvisation and Learning Judy A. Franklin
Using Vocabulary Knowledge in Bayesian Multinomial Estimation Thomas L. Griffiths, Joshua B. Tenenbaum
Cobot: A Social Reinforcement Learning Agent Charles Lee Isbell Jr., Christian R. Shelton
Optimising Synchronisation Times for Mobile Devices Neil D. Lawrence, Antony I. T. Rowstron, Christopher M. Bishop, Michael J. Taylor
Prodding the ROC Curve: Constrained Optimization of Classifier Performance Michael C. Mozer, Robert Dodier, Michael D. Colagrosso, Cesar Guerra-Salcedo, Richard Wolniewicz
Hyperbolic Self-Organizing Maps for Semantic Navigation Jorg Ontrup, Helge Ritter
Learning a Gaussian Process Prior for Automatically Generating Music Playlists John C. Platt, Christopher J. C. Burges, Steven Swenson, Christopher Weare, Alice Zheng
A Bayesian Network for Real-Time Musical Accompaniment Christopher Raphael
The Intelligent surfer: Probabilistic Combination of Link and Content Information in PageRank Matthew Richardson, Pedro Domingos
Active Learning in the Drug Discovery Process Manfred K. K. Warmuth, Gunnar Rätsch, Michael Mathieson, Jun Liao, Christian Lemmen
Face Recognition Using Kernel Methods Ming-Hsuan Yang
Active Portfolio-Management based on Error Correction Neural Networks Hans-Georg Zimmermann, Ralph Neuneier, Ralph Grothmann
Reinforcement Learning with Long Short-Term Memory Bram Bakker
Playing is believing: The role of beliefs in multi-agent learning Yu-Han Chang, Leslie Pack Kaelbling
Batch Value Function Approximation via Support Vectors Thomas G. Dietterich, Xin Wang
Convergence of Optimistic and Incremental Q-Learning Eyal Even-dar, Yishay Mansour
Variance Reduction Techniques for Gradient Estimates in Reinforcement Learning Evan Greensmith, Peter L. Bartlett, Jonathan Baxter
Rates of Convergence of Performance Gradient Estimates Using Function Approximation and Bias in Reinforcement Learning Gregory Z. Grudic, Lyle H. Ungar
Multiagent Planning with Factored MDPs Carlos Guestrin, Daphne Koller, Ronald Parr
A Natural Policy Gradient Sham M. Kakade
Incremental A* S. Koenig, M. Likhachev
Model-Free Least-Squares Policy Iteration Michail G. Lagoudakis, Ronald Parr
Predictive Representations of State Michael L. Littman, Richard S. Sutton
The Steering Approach for Multi-Criteria Reinforcement Learning Shie Mannor, Nahum Shimkin
Efficient Resources Allocation for Markov Decision Processes Rémi Munos
Direct value-approximation for factored MDPs Dale Schuurmans, Relu Patrascu
Stabilizing Value Function Approximation with the BFBP Algorithm Xin Wang, Thomas G. Dietterich