Book

Advances in Neural Information Processing Systems 14 (NIPS 2001)

Edited by: T. Dietterich and S. Becker and Z. Ghahramani

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

Advances in Neural Information Processing Systems 14 (NIPS 2001)

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