Advances in Neural Information Processing Systems 14 (NIPS 2001)

• 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