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Conference Materials

Neural Information Processing Systems 1999 (NIPS 12)

	Lightness Perception and Lightness Illusions (Banquet Talk) Edward H. Adelson Recurrent Cortical Competition: Strengthen or Weaken? Peter Adorjan, Lars Schwabe, Christian Piepenbrock and Klaus Obermayer Robust Full Bayesian Methods for Neural Networks Christophe Andrieu, Nando de Freitas and Arnaud Doucet Inferring Parameters and Structure of Graphical Models by Variational Bayes Hagai Attias Dynamic Graphical Models for Independent Factor Analysis Hagai Attias Robust Learning of Chaotic Attractors Rembrandt Bakker, Jaap C. Schouten, Floris Takens, C. Lee Giles and Cor M. van den Bleek Gaussian Fields for Approximate Inference in Layered Sigmoid Belief Networks David Barber and Peter Sollich Image Representations for Facial Action Coding Marian Stewart Bartlett, Gianluca Donato, Javier R. Movellan, Joseph C. Hager, Paul Ekman and Terrence J. Sejnowski Recognizing Evoked Potentials in a Virtual Environment Jessica D. Bayliss and Dana H. Ballard Modeling High-Dimensional Discrete Data with Multi-Layer Neural Networks Yoshua Bengio and Samy Bengio Robust Neural Network Regression for Offline and Online Learning Thomas Briegel and Volker Tresp An Oscillatory Correlation Framework for Computational Auditory Scene Analysis Guy J. Brown and DeLiang L. Wang Low Power Communications via Reinforcement Learning Timothy X. Brown Model Selection in Clustering by Uniform Convergence Bounds Joachim M. Buhmann and Marcus Held Uniqueness of the SVM Solution Chris Burges and David Crisp Reconstruction of Sequential Data with Probabilistic Models and Continuity Constraints Miguel A. Carreira-Perpinan Model Selection for Support Vector Machines Olivier Chapelle and Vladimir N. Vapnik Transductive Inference for Estimating Values of Functions Olivier Chapelle, Vladimir N. Vapnik and Jason Weston Effective Learning Requires Neuronal Remodeling of Hebbian Synapses Gal Chechik, Isaac Meilijson and Eytan Ruppin Optimal Sizes of Dendritic and Axonal Arbors Dmitri B. Chklovskii Wiring Optimization in the Brain Dmitri B. Chklovskii and Charles F. Stevens An Environment Model for Nonstationary Reinforcement Learning Samuel P. Choi, Dit-Yan Yeung and Nevin L. Zhang Dynamics of Supervised Learning with Restricted Training Sets and Noisy Teachers A.C.C. Coolen and C.W.H. Mace A Geometric Interpretation of nu-SVM Classifiers David Crisp and Chris Burges Efficient Approaches to Gaussian Process Classification Lehel Csato, Ernest Fokue, Manfred Opper, Bernhard Schottky and Ole Winthe A Neurodynamical Approach to Visual Attention Gustavo Deco and Josef Zih State Abstraction in MAXQ Hierarchical Reinforcement Learning Thomas G. Dietterich The Nonnegative Boltzmann Machine Oliver B. Downs, David J.C. MacKay and Daniel D. Lee Potential Boosters? Nigel Duffy and David Helmbold Sound Processing for Cochlear Implants: Rationale, Implementation and Patient Performance (Invited Talk) Donald K. Eddington Global Spatial Patterning Through Distance and Delay (Invited Talk) Bard Ermentrout Neural Representation of Multi-Dimensional Stimuli Christian W. Eurich, Stefan D. Wilke and Helmut Schwegler Learning Informative Statistics: A Nonparametric Approach John W. Fisher III, Alexander T. Ihler and Paul Viola Differentiating Functions of the Jacobian with Respect to the Weights Gary William Flake and Barak A. Pearlmutter Local Probability Propagation for Factor Analysis Brendan Frey Variational Inference for Bayesian Mixture of Factor Analysers Zoubin Ghahramani and Matthew J. Beal Effects of Spatial and Temporal Contiguity on the Acquisition of Spatial Information Thea Ghiselli-Crippa and Paul Munro Kirchoff Law Markov Fields for Analog Circuit Design Richard M. Golden Bayesian Transduction Thore Graepel, Ralf Herbrich and Klaus Obermayer Bayesian Averaging is Well-Temperated Lars Kai Hansen Audio Vision: Using Audio-Visual Synchrony to Locate Sounds John Hershey, Hiroshi Ishiguro and Javier R. Movellan Learning to Parse Images Geoffrey E. Hinton, Zoubin Ghahramani and Yee Whye Teh Spiking Belief Networks Geoffrey E. Hinton and Andrew D. Brown Animation of Human Motion (Invited talk) Jessica K. Hodgins Learning the Similarity of Documents: An Information-Geometric Approach to Document Retrieval and Categorization Thomas Hofmann Bayesian Modelling of fMRI Time Series Pedro Højen-Sørensen, Lars Kai Hansen and Carl Edward Rasmussen Distributed Synchrony of Spiking Neurons in a Hebbian Cell Assembly David Horn, Nir Levy, Isaac Meilijson and Eytan Ruppin Bayesian Reconstruction of 3D Human Motion from Single-Camera Video Nicholas R. Howe, Michael E. Leventon and William T. Freeman Emergence of Topography and Complex Cell Properties from Natural Images using Extensions of ICA Aapo Hyvärinen and Patrik Hoyer The Parallel Problems Server: an Interactive Tool for Large Scale Machine Learning Charles Lee Isbell, Jr. and Parry Husbands Maximum Entropy Discrimination Tommi Jaakkola, Marina Meila and Tony Jebara Neural System Model of Human Sound Localization Craig T. Jin and Simon Carlile Spectral Cues in Human Sound Localization Craig T. Jin, Anna Corderoy, Simon Carlile and André van Schaik Topographic Transformation as a Discrete Latent Variable Nebojsa Jojic and Brendan Frey Broadband DOA Estimation Based on Second Order Statistics Alexander Jourjine, Joseph O'Ruanaidh, Justinian Rosca and Scott Rickard Regular and Irregular Gallager-type Error-Correcting Codes Yoshiyuki Kabashima, Tatsuto Murayama, David Saad and Renato Vicente Acquisition in Autoshaping Sham Kakade and Peter Dayan Approximate Planning in Large POMDPs via Reusable Trajectories Michael Kearns, Yishay Mansour and Andrew Y. Ng Actor-Critic Algorithms Vijay R. Konda and John N. Tsitsiklis An Oculo-Motor System with Multi-Chip Neuromorphic Analog VLSI Control Oliver Landolt and Steve Gyger {An Improved Decomposition Algorithm for Regression Support Vector Machines Pavel Laskov Selective Attention for Robust Recognition of Noisy and Superimposed Patterns Soo-Young Lee and Michael C. Mozer Algorithms for Independent Components Analysis and Higher Order Statistics Daniel D. Lee, Uri Rokni and Haim Sompolinsky An Information-Theoretic Framework for Understanding Saccadic Behaviors Tai Sing Lee and Stella X. Yu Can V1 Mechanisms Account for Figure-Ground and Medial Axis Effects? Zhaoping Li Mixture Density Estimation Jonathan Q. Li and Andrew R. Barron Statistical Dynamics of Batch Learning Song Li and K.Y.Michael Wong The Relaxed Online Maximum Margin Algorithm Yi Li and Philip M. Long Constructing Heterogeneous Committees Using Input Feature Grouping: Application to Economic Forecasting Yuansong Liao and John Moody Perceptual Organization Based on Temporal Dynamics Xiuwen Liu and DeLiang L. Wang A Winner-Take-All Circuit with Controlable Soft Max Property Shih-Chii Liu How Anomalous are Anomalies in Financial Time Series? (Invited Talk) Andrew W. Lo and Li Jin Neural Computation with Winner-Take-All as the Only Nonlinear Operation Wolfgang Maass Boosting with Multi-Way Branching in Decision Trees Yishay Mansour and David McAllester Channel Noise in Excitable Neural Membranes Amit Manwani, Peter N. Steinmetz and Christof Koch Bayesian Network Induction via Local Neighborhoods Dimitris Margaritis and Sebastian Thrun Boosting Algorithms as Gradient Descent Llew Mason, Jonathan Baxter, Peter Bartlett and Marcus Frean A Multi-class Linear Learning Algorithm Chris Mesterharm Invariant Feature Extraction and Classification in Kernel Spaces Sebastian Mika, Gunnar Rätsch, Jason Weston, Bernhard Schölkopf, Alexander J. Smola and Klaus--Robert Müller From Coexpression to Coregulation: An Approach to Inferring Transcriptional Regulation among Gene Classes from Large-Scale Expression Data Eric Mjolsness, Tobias Mann, Rebecca Castano and Barbara Wold Information Factorization in Connectionist Models of Perception Javier R. Movellan and James L. McClelland Deconstructing Synchrony (Invited Talk) J. Anthony Movshon Churn Reduction in the Wireless Industry Michael C. Mozer, Richard Wolniewicz, David Grimes, Eric Johnson and Howard Kaushansky LTD Facilitates Learning in a Noisy Environment Paul Munro and Gerardina Hernandez Bayesian Map Learning in Dynamic Environments Kevin Murphy Inference for the Generalization Error Claude Nadeau and Yoshua Bengio Policy Search via Density Estimation Andrew Y. Ng, Ronald Parr and Daphne Koller Approximate Inference Algorithms for Two-Layer Bayesian Networks Andrew Y. Ng and Michael Jordan Resonance in Stochastic Neuron Model with Delayed Interaction Toru Ohir, Yuzuru Sato and Jack D. Cowan Learning Sparse Codes with a Mixture-of-Gaussians Prior Bruno A. Olshausen and K. Jarrod Millman Optimal Kernel Shapes for Local Linear Regression Dirk Ormoneit and Trevor Hastie Graded Grammaticality in Prediction Fractal Machines Shan Parfitt, Peter Tino and Georg Dorffner Unmixing Hyperspectral Data Lucas Parra, Clay Spence, Paul Sajda, Andreas Ziehe and Klaus--Robert Müller A Neuromorphic VLSI System for Modeling the Neural Control of Axial Locomotion Girish N. Patel, Edgar A. Brown and Stephen P. DeWeerth Bifurcation Analysis of a Silicon Neuron Girish N. Patel, Gennady S. Cymbalyuk, Ronald L. Calabrese and Stephen P. DeWeerth Neural Network Based Model Predictive Control Stephen Piche, Jim Keeler, Greg Martin, Gene Boe, Doug Johnson and Mark Gerules Large Margin DAGs for Multiclass Classification John C. Platt, Nello Cristianini and John Shawe-Taylor Memory Capacity of Linear vs. Nonlinear Models of Dendritic Integration Panayiota Poirazi and Bartlett W. Mel Predictive Sequence Learning in Recurrent Neocortical Circuits Rajesh P. N. Rao and Terrence J. Sejnowski The Infinite Gaussian Mixture Model Carl Edward Rasmussen nu-Arc: Ensemble Learning in the Presence of Outliers Gunnar Rätsch, Bernhard Schölkopf, Alexander J. Smola, Klaus--Robert Müller, Takashi Onoda and Sebastian Mika A Recurrent Model of the Interaction Between Prefrontal and Inferotemporal Cortex in Delay Tasks Alfonso Renart, Nestor Parga and Edmund T. Rolls Understanding Stepwise Generalization of Support Vector Machines: a Toy Model Sebastian Risau-Gusman and Mirta B. Gordon Reinforcement Learning Using Approximate Belief States Andrés Rodríguez, Ronald Parr and Daphne Koller Nonlinear Discriminant Analysis Using Kernel Functions Volker Roth and Volker Steinhage A SNoW-Based Face Detector Dan Roth, Ming-Hsuan Yang and Narendra Ahuja Constrained Hidden Markov Models Sam Roweis Coastal Navigation with Mobile Robots Nicholas Roy and Sebastian Thrun An Analysis of Turbo Decoding with Gaussian Densitie Paat Rusmevichientong and Benjamin Van Roy Learning Factored Representations for Partially Observable Markov Decision Processes Brian Sallans Lower Bounds on the Complexity of Approximating Continuous Functions by Sigmoidal Neural Networks Michael Schmitt Information Capacity and Robustness of Stochastic Neuron Models Elad Schneidman, Idan Segev and Naftali Tishby Application of Blind Separation of Sources to Optical Recording of Brain Activity Holger Schoener, Martin Stetter, Ingo Schießl, Jennifer Lund, Niall McLoughlin, John E.W. Mayhew and Klaus Obermayer SV Estimation of a Distribution's Support Bernhard Schölkopf, Robert C. Williamson and John Shawe-Taylor Online Independent Component Analysis with Local Learning Rate Adaptation Nicol N. Schraudolph and Xavier Giannakopoulos Better Generative Models for Sequential Data Problems: Bidirectional Recurrent Mixture Density Networks Mike Schuster Greedy Importance Sampling Dale Schuurmans Bayesian Model Selection for Support Vector Machines, Gaussian Processes and Other Kernel Classifiers Matthias Seeger Noisy Neural Networks and Generalizations Hava T. Siegelmann, Alexander Roiterstein and Asa Ben-Hur Leveraged Vector Machines Yoram Singer Reinforcement Learning for Spoken Dialogue Systems Satinder Singh, Michael Kearns and Marilyn Walker Agglomerative Information Bottleneck Noam Slonim and Naftali Tishby Speech Modelling Using Subspace and EM Techniques Gavin Smith, Nando de Freitas, Tony Robinson and Mahesan Niranjan The Entropy Regularization Information Criterion Alexander J. Smola, John Shawe-Taylor, Bernhard Schölkopf and Robert C. Williamson Probabilistic Methods for Support Vector Machines Peter Sollich Image Recognition in Context: Application to Microscopic Urinalysis Xubo B. Song, Yaser Abu-Mostafa, Joseph Sill and Harvey Kasdan Hierarchical Image Probability (HIP) Models Clay Spence and Lucas Parra Training Data Selection for Optimal Generalization in Trigonometric Polynomial Networks Masashi Sugiyama and Hidemitsu Ogawa Predictive Approaches for Choosing Hyperparameters in Gaussian Processes S. Sundararajan and S. Sathiya Keerthi Policy Gradient Methods for Reinforcement Learning with Function Approximation Richard S. Sutton, David McAllester, Satinder Singh and Yishay Mansour On Input Selection with Reversible Jump Markov Chain Monte Carlo Peter Sykacek A MEG Study of Response Latency and Variability in the Human Visual System Akaysha C. Tang, Barak A. Pearlmutter, Tim A. Hely, Michael P. Weisend and Michael Zibulevsky Rules and Similarity in Concept Learning Joshua B. Tenenbaum Monte Carlo POMDPs Sebastian Thrun Building Predictive Models from Spatial Representations of Symbolic Sequences Peter Tino and Georg Dorffner The Relevance Vector Machine Michael E. Tipping Evolving Learnable Languages Bradley Tonkes, Alan Blair and Janet Wiles Generalized Model Selection for Unsupervised Learning in High Dimensions Shivakumar Vaithyanathan and Byron Dom An Analog VLSI Model of Periodicity Extraction André van Schaik Support Vector Method for Multivariate Density Estimation Vladimir N. Vapnik and Sayan Mukherjee Learning from User Feedback in Image Retrieval Systems Nuno Vasconcelos and Andrew Lippman Scale Mixtures of Gaussians and the Statistics of Natural Images Martin J. Wainwright and Eero P. Simoncelli Dual Estimation and the Unscented Transformation Eric A. Wan, Rudolph van der Merwe and Alex T. Nelson Algebraic Analysis for Non-regular Learning Machines Sumio Watanabe Learning Statistically Neutral Tasks without Expert Guidance Ton Weijters, Antal van den Bosch and Eric Postma Correctness of Belief Propagation in Gaussian Graphical Models of Arbitrary Topology Yair Weiss and William T. Freeman Probabilistic Hierarchical Clustering Christopher K. I. Williams Using Collective Intelligence to Route Internet Traffic David Wolpert, Kagan Tumer and Jeremy Frank Population Decoding Based on an Unfaithful Model Si Wu, Hiroyuki Nakahara, Noboru Murata and Shun-ichi Amari Spike-based Learning Rules and Stabilization of Persistent Neural Activity Xiao-Hui Xie and H. Sebastian Seung Search for Information Bearing Components in Speech Howard Hua Yang and Hynek Hermansky A Generative Model for Visual Cue Combination Zhiyong Yang and Richard S. Zemel Data Visualization and Feature Selection: New Algorithms for Nongaussian Data Howard Hua Yang and John Moody Localist Attractor Networks Richard S. Zemel and Michael C. Mozer Some Theoretical Results Concerning the Convergence of Compositions of Regularized Linear Functions Tong Zhang Blind Deconvolution of Nonminimum Phase Systems L.-Q. Zhang, Shun-ichi Amari and A. Cichocki Manifold Stochastic Dynamics for Bayesian Learning Mark Zlochin and Yoram Baram

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