NeurIPS 1999

150 papers

A Generative Model for Attractor Dynamics Richard S. Zemel, Michael Mozer

A Geometric Interpretation of V-SVM Classifiers David J. Crisp, Christopher J. C. Burges

A MCMC Approach to Hierarchical Mixture Modelling Christopher K. I. Williams

A Multi-Class Linear Learning Algorithm Related to Winnow Chris Mesterharm

A Neurodynamical Approach to Visual Attention Gustavo Deco, Josef Zihl

A Neuromorphic VLSI System for Modeling the Neural Control of Axial Locomotion Girish N. Patel, Edgar A. Brown, Stephen P. DeWeerth

A Recurrent Model of the Interaction Between Prefrontal and Inferotemporal Cortex in Delay Tasks Alfonso Renart, Néstor Parga, Edmund T. Rolls

A SNoW-Based Face Detector Ming-Hsuan Yang, Dan Roth, Narendra Ahuja

A Variational Baysian Framework for Graphical Models Hagai Attias

A Winner-Take-All Circuit with Controllable Soft Max Property Shih-Chii Liu

Acquisition in Autoshaping Sham Kakade, Peter Dayan

Actor-Critic Algorithms Vijay R. Konda, John N. Tsitsiklis

Agglomerative Information Bottleneck Noam Slonim, Naftali Tishby

Algebraic Analysis for Non-Regular Learning Machines Sumio Watanabe

Algorithms for Independent Components Analysis and Higher Order Statistics Daniel D. Lee, Uri Rokni, Haim Sompolinsky

An Analog VLSI Model of Periodicity Extraction André van Schaik

An Analysis of Turbo Decoding with Gaussian Densities Paat Rusmevichientong, Benjamin Van Roy

An Environment Model for Nonstationary Reinforcement Learning Samuel P. M. Choi, Dit-Yan Yeung, Nevin Lianwen Zhang

An Improved Decomposition Algorithm for Regression Support Vector Machines Pavel Laskov

An Information-Theoretic Framework for Understanding Saccadic Eye Movements Tai Sing Lee, Stella X. Yu

An MEG Study of Response Latency and Variability in the Human Visual System During a Visual-Motor Integration Task Akaysha C. Tang, Barak A. Pearlmutter, Tim A. Hely, Michael Zibulevsky, Michael P. Weisend

An Oculo-Motor System with Multi-Chip Neuromorphic Analog VLSI Control Oliver Landolt, Steve Gyger

An Oscillatory Correlation Frame Work for Computational Auditory Scene Analysis Guy J. Brown, DeLiang L. Wang

Application of Blind Separation of Sources to Optical Recording of Brain Activity Holger Schoner, Martin Stetter, Ingo Schießl, John E. W. Mayhew, Jennifer S. Lund, Niall McLoughlin, Klaus Obermayer

Approximate Inference a Lgorithms for Two-Layer Bayesian Networks Andrew Y. Ng, Michael I. Jordan

Approximate Planning in Large POMDPs via Reusable Trajectories Michael J. Kearns, Yishay Mansour, Andrew Y. Ng

Audio Vision: Using Audio-Visual Synchrony to Locate Sounds John R. Hershey, Javier R. Movellan

Bayesian Averaging Is Well-Temperated Lars Kai Hansen

Bayesian mAP Learning in Dynamic Environments Kevin P. Murphy

Bayesian Model Selection for Support Vector Machines, Gaussian Processes and Other Kernel Classifiers Matthias Seeger

Bayesian Modelling of fMRI Lime Series Pedro A. d. F. R. Højen-Sørensen, Lars Kai Hansen, Carl Edward Rasmussen

Bayesian Network Induction via Local Neighborhoods Dimitris Margaritis, Sebastian Thrun

Bayesian Reconstruction of 3D Human Motion from Single-Camera Video Nicholas R. Howe, Michael E. Leventon, William T. Freeman

Bayesian Transduction Thore Graepel, Ralf Herbrich, Klaus Obermayer

Better Generative Models for Sequential Data Problems: Bidirectional Recurrent Mixture Density Networks Mike Schuster

Bifurcation Analysis of a Silicon Neuron Girish N. Patel, Gennady S. Cymbalyuk, Ronald L. Calabrese, Stephen P. DeWeerth

Boosting Algorithms as Gradient Descent Llew Mason, Jonathan Baxter, Peter L. Bartlett, Marcus R. Frean

Boosting with Multi-Way Branching in Decision Trees Yishay Mansour, David A. McAllester

Broadband Direction-of-Arrival Estimation Based on Second Order Statistics Justinian P. Rosca, Joseph Ó Ruanaidh, Alexander Jourjine, Scott Rickard

Building Predictive Models from Fractal Representations of Symbolic Sequences Peter Tiño, Georg Dorffner

Can VI Mechanisms Account for Figure-Ground and Medial Axis Effects? Zhaoping Li

Channel Noise in Excitable Neural Membranes Amit Manwani, Peter N. Steinmetz, Christof Koch

Churn Reduction in the Wireless Industry Michael Mozer, Richard H. Wolniewicz, David B. Grimes, Eric Johnson, Howard Kaushansky

Coastal Navigation with Mobile Robots Nicholas Roy, Sebastian Thrun

Constrained Hidden Markov Models Sam T. Roweis

Constructing Heterogeneous Committees Using Input Feature Grouping: Application to Economic Forecasting Yuansong Liao, John E. Moody

Correctness of Belief Propagation in Gaussian Graphical Models of Arbitrary Topology Yair Weiss, William T. Freeman

Data Visualization and Feature Selection: New Algorithms for Nongaussian Data Howard Hua Yang, John Moody

Differentiating Functions of the Jacobian with Respect to the Weights Gary William Flake, Barak A. Pearlmutter

Distributed Synchrony of Spiking Neurons in a Hebbian Cell Assembly David Horn, Nir Levy, Isaac Meilijson, Eytan Ruppin

Dual Estimation and the Unscented Transformation Eric A. Wan, Rudolph van der Merwe, Alex T. Nelson

Dynamics of Supervised Learning with Restricted Training Sets and Noisy Teachers Anthony C. C. Coolen, C. W. H. Mace

Effective Learning Requires Neuronal Remodeling of Hebbian Synapses Gal Chechik, Isaac Meilijson, Eytan Ruppin

Effects of Spatial and Temporal Contiguity on the Acquisition of Spatial Information Thea B. Ghiselli-Crippa, Paul W. Munro

Efficient Approaches to Gaussian Process Classification Lehel Csató, Ernest Fokoué, Manfred Opper, Bernhard Schottky, Ole Winther

Emergence of Topography and Complex Cell Properties from Natural Images Using Extensions of ICA Aapo Hyvärinen, Patrik O. Hoyer

Evolving Learnable Languages Bradley Tonkes, Alan Blair, Janet Wiles

From Coexpression to Coregulation: An Approach to Inferring Transcriptional Regulation Among Gene Classes from Large-Scale Expression Data Eric Mjolsness, Tobias Mann, Rebecca Castaño, Barbara J. Wold

Gaussian Fields for Approximate Inference in Layered Sigmoid Belief Networks David Barber, Peter Sollich

Generalized Model Selection for Unsupervised Learning in High Dimensions Shivakumar Vaithyanathan, Byron Dom

Graded Grammaticality in Prediction Fractal Machines Shan Parfitt, Peter Tiño, Georg Dorffner

Greedy Importance Sampling Dale Schuurmans

Hierarchical Image Probability (H1P) Models Clay Spence, Lucas C. Parra

Image Recognition in Context: Application to Microscopic Urinalysis Xubo B. Song, Joseph Sill, Yaser S. Abu-Mostafa, Harvey Kasdan

Image Representations for Facial Expression Coding Marian Stewart Bartlett, Gianluca Donato, Javier R. Movellan, Joseph C. Hager, Paul Ekman, Terrence J. Sejnowski

Independent Factor Analysis with Temporally Structured Sources Hagai Attias

Inference for the Generalization Error Claude Nadeau, Yoshua Bengio

Information Capacity and Robustness of Stochastic Neuron Models Elad Schneidman, Idan Segev, Naftali Tishby

Information Factorization in Connectionist Models of Perception Javier R. Movellan, James L. McClelland

Invariant Feature Extraction and Classification in Kernel Spaces Sebastian Mika, Gunnar Rätsch, Jason Weston, Bernhard Schölkopf, Alex J. Smola, Klaus-Robert Müller

Kirchoff Law Markov Fields for Analog Circuit Design Richard M. Golden

Large Margin DAGs for Multiclass Classification John C. Platt, Nello Cristianini, John Shawe-Taylor

Learning Factored Representations for Partially Observable Markov Decision Processes Brian Sallans

Learning from User Feedback in Image Retrieval Systems Nuno Vasconcelos, Andrew Lippman

Learning Informative Statistics: A Nonparametnic Approach John W. Fisher Iii, Alexander T. Ihler, Paul A. Viola

Learning Sparse Codes with a Mixture-of-Gaussians Prior Bruno A. Olshausen, K. Jarrod Millman

Learning Statistically Neutral Tasks Without Expert Guidance Ton Weijters, Antal van den Bosch, Eric O. Postma

Learning the Similarity of Documents: An Information-Geometric Approach to Document Retrieval and Categorization Thomas Hofmann

Learning to Parse Images Geoffrey E. Hinton, Zoubin Ghahramani, Yee Whye Teh

Leveraged Vector Machines Yoram Singer

Local Probability Propagation for Factor Analysis Brendan J. Frey

Low Power Wireless Communication via Reinforcement Learning Timothy X. Brown

Lower Bounds on the Complexity of Approximating Continuous Functions by Sigmoidal Neural Networks Michael Schmitt

LTD Facilitates Learning in a Noisy Environment Paul W. Munro, Gerardina Hernández

Managing Uncertainty in Cue Combination Zhiyong Yang, Richard S. Zemel

Manifold Stochastic Dynamics for Bayesian Learning Mark Zlochin, Yoram Baram

Maximum Entropy Discrimination Tommi Jaakkola, Marina Meila, Tony Jebara

Memory Capacity of Linear vs. Nonlinear Models of Dendritic Integration Panayiota Poirazi, Bartlett W. Mel

Mixture Density Estimation Jonathan Q. Li, Andrew R. Barron

Model Selection for Support Vector Machines Olivier Chapelle, Vladimir Vapnik

Model Selection in Clustering by Uniform Convergence Bounds Joachim M. Buhmann, Marcus Held

Modeling High-Dimensional Discrete Data with Multi-Layer Neural Networks Yoshua Bengio, Samy Bengio

Monte Carlo POMDPs Sebastian Thrun

Neural Computation with Winner-Take-All as the Only Nonlinear Operation Wolfgang Maass

Neural Network Based Model Predictive Control Stephen Piche, James D. Keeler, Greg Martin, Gene Boe, Doug Johnson, Mark Gerules

Neural Representation of Multi-Dimensional Stimuli Christian W. Eurich, Stefan D. Wilke, Helmut Schwegler

Neural System Model of Human Sound Localization Craig T. Jin, Simon Carlile

Noisy Neural Networks and Generalizations Hava T. Siegelmann, Alexander Roitershtein, Asa Ben-Hur

Nonlinear Discriminant Analysis Using Kernel Functions Volker Roth, Volker Steinhage

On Input Selection with Reversible Jump Markov Chain Monte Carlo Sampling Peter Sykacek

Online Independent Component Analysis with Local Learning Rate Adaptation Nicol N. Schraudolph, Xavier Giannakopoulos

Optimal Kernel Shapes for Local Linear Regression Dirk Ormoneit, Trevor Hastie

Optimal Sizes of Dendritic and Axonal Arbors Dmitri B. Chklovskii

Perceptual Organization Based on Temporal Dynamics Xiuwen Liu, DeLiang L. Wang

Policy Gradient Methods for Reinforcement Learning with Function Approximation Richard S. Sutton, David A. McAllester, Satinder P. Singh, Yishay Mansour

Policy Search via Density Estimation Andrew Y. Ng, Ronald Parr, Daphne Koller

Population Decoding Based on an Unfaithful Model Si Wu, Hiroyuki Nakahara, Noboru Murata, Shun-ichi Amari

Potential Boosters? Nigel Duffy, David P. Helmbold

Predictive App Roaches for Choosing Hyperparameters in Gaussian Processes S. Sundararajan, S. Sathiya Keerthi

Predictive Sequence Learning in Recurrent Neocortical Circuits Rajesh P. N. Rao, Terrence J. Sejnowski

Probabilistic Methods for Support Vector Machines Peter Sollich

Recognizing Evoked Potentials in a Virtual Environment Jessica D. Bayliss, Dana H. Ballard

Reconstruction of Sequential Data with Probabilistic Models and Continuity Constraints Miguel Á. Carreira-Perpiñán

Recurrent Cortical Competition: Strengthen or Weaken? Péter Adorján, Lars Schwabe, Christian Piepenbrock, Klaus Obermayer

Regular and Irregular Gallager-Zype Error-Correcting Codes Yoshiyuki Kabashima, Tatsuto Murayama, David Saad, Renato Vicente

Reinforcement Learning for Spoken Dialogue Systems Satinder P. Singh, Michael J. Kearns, Diane J. Litman, Marilyn A. Walker

Reinforcement Learning Using Approximate Belief States Andres C. Rodriguez, Ronald Parr, Daphne Koller

Resonance in a Stochastic Neuron Model with Delayed Interaction Toru Ohira, Yuzuru Sato, Jack D. Cowan

Robust Full Bayesian Methods for Neural Networks Christophe Andrieu, João F. G. de Freitas, Arnaud Doucet

Robust Learning of Chaotic Attractors Rembrandt Bakker, Jaap C. Schouten, Marc-Olivier Coppens, Floris Takens, C. Lee Giles, Cor M. van den Bleek

Robust Neural Network Regression for Offline and Online Learning Thomas Briegel, Volker Tresp

Robust Recognition of Noisy and Superimposed Patterns via Selective Attention Soo-Young Lee, Michael Mozer

Rules and Similarity in Concept Learning Joshua B. Tenenbaum

Scale Mixtures of Gaussians and the Statistics of Natural Images Martin J. Wainwright, Eero P. Simoncelli

Search for Information Bearing Components in Speech Howard Hua Yang, Hynek Hermansky

Semiparametric Approach to Multichannel Blind Deconvolution of Nonminimum Phase Systems Liqing Zhang, Shun-ichi Amari, Andrzej Cichocki

Some Theoretical Results Concerning the Convergence of Compositions of Regularized Linear Functions Tong Zhang

Spectral Cues in Human Sound Localization Craig T. Jin, Anna Corderoy, Simon Carlile, André van Schaik

Speech Modelling Using Subspace and EM Techniques Gavin Smith, João F. G. de Freitas, Tony Robinson, Mahesan Niranjan

Spike-Based Learning Rules and Stabilization of Persistent Neural Activity Xiaohui Xie, H. Sebastian Seung

Spiking Boltzmann Machines Geoffrey E. Hinton, Andrew D. Brown

State Abstraction in MAXQ Hierarchical Reinforcement Learning Thomas G. Dietterich

Statistical Dynamics of Batch Learning Song Li, K. Y. Michael Wong

Support Vector Method for Multivariate Density Estimation Vladimir Vapnik, Sayan Mukherjee

Support Vector Method for Novelty Detection Bernhard Schölkopf, Robert C. Williamson, Alex J. Smola, John Shawe-Taylor, John C. Platt

The Entropy Regularization Information Criterion Alex J. Smola, John Shawe-Taylor, Bernhard Schölkopf, Robert C. Williamson

The Infinite Gaussian Mixture Model Carl Edward Rasmussen

The Nonnegative Boltzmann Machine Oliver B. Downs, David J. C. MacKay, Daniel D. Lee

The Parallel Problems Server: An Interactive Tool for Large Scale Machine Learning Charles Lee Isbell Jr., Parry Husbands

The Relaxed Online Maximum Margin Algorithm Yi Li, Philip M. Long

The Relevance Vector Machine Michael E. Tipping

Topographic Transformation as a Discrete Latent Variable Nebojsa Jojic, Brendan J. Frey

Training Data Selection for Optimal Generalization in Trigonometric Polynomial Networks Masashi Sugiyama, Hidemitsu Ogawa

Transductive Inference for Estimating Values of Functions Olivier Chapelle, Vladimir Vapnik, Jason Weston

Understanding Stepwise Generalization of Support Vector Machines: A Toy Model Sebastian Risau-Gusman, Mirta B. Gordon

Uniqueness of the SVM Solution Christopher J. C. Burges, David J. Crisp

Unmixing Hyperspectral Data Lucas C. Parra, Clay Spence, Paul Sajda, Andreas Ziehe, Klaus-Robert Müller

V-Arc: Ensemble Learning in the Presence of Outliers Gunnar Rätsch, Bernhard Schölkopf, Alex J. Smola, Klaus-Robert Müller, Takashi Onoda, Sebastian Mika

Variational Inference for Bayesian Mixtures of Factor Analysers Zoubin Ghahramani, Matthew J. Beal

Wiring Optimization in the Brain Dmitri B. Chklovskii, Charles F. Stevens