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NIPS*1999
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| Title Pages [ps][pdf][djvu] Recognizing Evoked Potentials in a Virtual Environment, Jessica D. Bayliss and Dana H. Ballard [ps][pdf][djvu] A Neurodynamical Approach to Visual Attention, Gustavo Deco and Josef Zihl [ps][pdf][djvu] Effects of Spatial and Temporal Contiguity on the Acquisition of Spatial Information, Thea B. Ghiselli-Crippa and Paul W. Munro [ps][pdf][djvu] Acquisition in Autoshaping, Sham Kakade and Peter Dayan [ps][pdf][djvu] Robust Recognition of Noisy and Superimposed Patterns via Selective Attention, Soo-Young Lee and Michael C. Mozer [ps][pdf][djvu] Perceptual Organization Based on Temporal Dynamics, Xiuwen Liu and DeLiang L. Wang [ps][pdf][djvu] Information Factorization in Connectionist Models of Perception, Javier R. Movellan and James L. McClelland [ps][pdf][djvu] Graded Grammaticality in Prediction Fractal Machines, Shan Parfitt, Peter Tino and Georg Dorffner [ps][pdf][djvu] Rules and Similarity in Concept Learning, Joshua B. Tenenbaum [ps][pdf][djvu] Evolving Learnable Languages, Bradley Tonkes, Alan Blair and Janet Wiles [ps][pdf][djvu] Learning Statistically Neutral Tasks without Expert Guidance, Ton Weijters, Antal van den Bosch and Eric Postma [ps][pdf][djvu] A Generative Model for Attractor Dynamics, Richard S. Zemel and Michael C. Mozer [ps][pdf][djvu] Recurrent Cortical Competition: Strengthen or Weaken?, Peter Adorjan, Lars Schwabe, Christian Piepenbrock and Klaus Obermayer [ps][pdf][djvu] Effective Learning Requires Neuronal Remodeling of Hebbian Synapses, Gal Chechik, Isaac Meilijson and Eytan Ruppin [ps][pdf][djvu] Wiring Optimization in the Brain, Dmitri B. Chklovskii and Charles F. Stevens [ps][pdf][djvu] Optimal Sizes of Dendritic and Axonal Arbors, Dmitri B. Chklovskii [ps][pdf][djvu] Neural Representation of Multi-Dimensional Stimuli, Christian W. Eurich, Stefan D. Wilke and Helmut Schwegler [ps][pdf][djvu] Spiking Boltzmann Machines, Geoffrey E. Hinton and Andrew D. Brown [ps][pdf][djvu] Distributed Synchrony of Spiking Neurons in a Hebbian Cell Assembly, David Horn, Nir Levy, Isaac Meilijson and Eytan Ruppin [ps][pdf][djvu] Can VI Mechanisms Account for Figure-Ground and Medial Axis Effects?, Zhaoping Li [ps][pdf][djvu] Channel Noise in Excitable Neural Membranes, Amit Manwani, Peter N. Steinmetz and Christof Koch [ps][pdf][djvu] LTD Facilitates Learning in a Noisy Environment, Paul W. Munro and Gerardina Hernandez [ps][pdf][djvu] Memory Capacity of Linear vs. Nonlinear Models of Dendritic Integration, Panayiota Poirazi and Bartlett W. Mel [ps][pdf][djvu] Predictive Sequence Learning in Recurrent Neocortical Circuits, Rajesh P. N. Rao and Terrence J. Sejnowski [ps][pdf][djvu] A Recurrent Model of the Interaction Between Prefrontal and Inferotemporal Cortex in Delay Tasks, Alfonso Renart, Nestor Parga and Edmund T. Rolls [ps][pdf][djvu] Information Capacity and Robustness of Stochastic Neuron Models, Elad Schneidman, Idan Segev and Naftali Tishby [ps][pdf][djvu] 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 and Michael P. Weisend [ps][pdf][djvu] Population Decoding Based on an Unfaithful Model, Si Wu, Hiroyuki Nakahara, Noboru Murata and Shun-ichi Amari [ps][pdf][djvu] Spike-based Learning Rules and Stabilization of Persistent Neural Activity, Xiaohui Xie and H. Sebastian Seung [ps][pdf][djvu] A Variational Baysian Framework for Graphical Models, Hagai Attias [ps][pdf][djvu] Model Selection in Clustering by Uniform Convergence Bounds, Joachim M. Buhmann and Marcus Held [ps][pdf][djvu] Uniqueness of the SVM Solution, Christopher J. C. Burges and David J. Crisp [ps][pdf][djvu] Model Selection for Support Vector Machines, Olivier Chapelle and Vladimir N. Vapnik [ps][pdf][djvu] Dynamics of Supervised Learning with Restricted Training Sets and Noisy Teachers, A. C. C. Coolen and C. W. H. Mace [ps][pdf][djvu] A Geometric Interpretation of v-SVM Classifiers, David J. Crisp and Christopher J. C. Burges [ps][pdf][djvu] Efficient Approaches to Gaussian Process Classification, Lehel Csato, Ernest Fokoue, Manfred Opper, Bernhard Schottky and Ole Winther [ps][pdf][djvu] Potential Boosters?, Nigel Duffy and David Helmbold [ps][pdf][djvu] Bayesian Averaging is Well-Temperated, Lars Kai Hansen [ps][pdf][djvu] Regular and Irregular Gallager-zype Error-Correcting Codes, Yoshiyuki Kabashima, Tatsuto Murayama, David Saad and Renato Vicente [ps][pdf][djvu] Mixture Density Estimation, Jonathan Q. Li and Andrew R. Barron [ps][pdf][djvu] Statistical Dynamics of Batch Learning, Song Li and K. Y. Michael Wong [ps][pdf][djvu] Neural Computation with Winner-Take-All as the Only Nonlinear Operation, Wolfgang Maass [ps][pdf][djvu] Boosting with Multi-Way Branching in Decision Trees, Yishay Mansour and David McAllester [ps][pdf][djvu] Inference for the Generalization Error Claude Nadeau and Yoshua Bengio [ps][pdf][djvu] Resonance in a Stochastic Neuron Model with Delayed Interaction, Toru Ohira, Yuzuru Sato and Jack D. Cowan [ps][pdf][djvu] Understanding Stepwise Generalization of Support Vector Machines: a Toy Model, Sebastian Risau-Gusman and Mirta B. Gordon [ps][pdf][djvu] Lower Bounds on the Complexity of Approximating Continuous Functions by Sigmoidal Neural Networks, Michael Schmitt [ps][pdf][djvu] Noisy Neural Networks and Generalizations, Hava T. Siegelmann, Alexander Roitershtein and Asa Ben-Hur [ps][pdf][djvu] The Entropy Regularization Information Criterion, Alexander J. Smola, John Shawe-Taylor, Bernhard Scholkopf and Robert C. Williamson [ps][pdf][djvu] Probabilistic Methods for Support Vector Machines, Peter Sollich [ps][pdf][djvu] Algebraic Analysis for Non-regular Learning Machines, Sumio Watanabe [ps][pdf][djvu] Semiparametric Approach to Multichannel Blind Deconvolution of Nonminimum Phase Systems, L. Q. Zhang, Shun-ichi Amari and A. Cichocki [ps][pdf][djvu] Some Theoretical Results Concerning the Convergence of Compositions of Regularized Linear Functions, Tong Zhang [ps][pdf][djvu] Robust Full Bayesian Methods for Neural Networks, Christophe Andrieu, Joao F. G. de Freitas and Arnaud Doucet [ps][pdf][djvu] Independent Factor Analysis with Temporally Structured Sources, Hagai Attias [ps][pdf][djvu] Gaussian Fields for Approximate Inference in Layered Sigmoid Belief Networks, David Barber and Peter Sollich [ps][pdf][djvu] Modeling High-Dimensional Discrete Data with Multi-Layer Neural Networks, Yoshua Bengio and Samy Bengio [ps][pdf][djvu] Robust Neural Network Regression for Offline and Online Learning, Thomas Briegel and Volker Tresp [ps][pdf][djvu] Reconstruction of Sequential Data with Probabilistic Models and Continuity Constraints, Miguel A. Carreira-Perpinan [ps][pdf][djvu] Transductive Inference for Estimating Values of Functions, Olivier Chapelle, Vladimir N. Vapnik and Jason Weston [ps][pdf][djvu] The Nonnegative Boltzmann Machine, Oliver B. Downs, David J.C. MacKay and Daniel D. Lee [ps][pdf][djvu] Differentiating Functions of the Jacobian with Respect to the Weights, Gary William Flake and Barak A. Pearlmutter [ps][pdf][djvu] Local Probability Propagation for Factor Analysis, Brendan J. Frey [ps][pdf][djvu] Variational Inference for Bayesian Mixtures of Factor Analysers, Zoubin Ghahramani and Matthew J. Beal [ps][pdf][djvu] Bayesian Transduction, Thore Graepel, Ralf Herbrich and Klaus Obermayer [ps][pdf][djvu] Learning to Parse Images, Geoffrey E. Hinton, Zoubin Ghahramani and Yee Whye Teh [ps][pdf][djvu] Maximum Entropy Discrimination, Tommi Jaakkola, Marina Meila and Tony Jebara [ps][pdf][djvu] Topographic Transformation as a Discrete Latent Variable, Nebojsa Jojic and Brendan J. Frey [ps][pdf][djvu] An Improved Decomposition Algorithm for Regression Support Vector Machines, Pavel Laskov [ps][pdf][djvu] Algorithms for Independent Components Analysis and Higher Order Statistics, Daniel D. Lee, Uri Rokni and Haim Sompolinsky [ps][pdf][djvu] The Relaxed Online Maximum Margin Algorithm, Yi Li and Philip M. Long [ps][pdf][djvu] Bayesian Network Induction via Local Neighborhoods, Dimitris Margaritis and Sebastian Thrun [ps][pdf][djvu] Boosting Algorithms as Gradient Descent, Liew Mason, Jonathan Baxter, Peter Bartlett and Marcus Frean [ps][pdf][djvu] A Multi-class Linear Learning Algorithm Related to Winnow, Chris Mesterharm [ps][pdf][djvu] Invariant Feature Extraction and Classification in Kernel Spaces, Sebastian Mika, Gunnar R\344tsch, Jason Weston, Bernhard Scholkopf, Alexander J. Smola and Klaus-Robert Muller [ps][pdf][djvu] Approximate Inference A lgorithms for Two-Layer Bayesian Networks, Andrew Y. Ng and Michael I. Jordan [ps][pdf][djvu] Optimal Kernel Shapes for Local Linear Regression, Dirk Ormoneit and Trevor Hastie [ps][pdf][djvu] Large Margin DAGs for Multiclass Classification, John C. Platt, Nello Cristianini and John Shawe-Taylor [ps][pdf][djvu] The Infinite Gaussian Mixture Model, Carl Edward Rasmussen [ps][pdf][djvu] v-Arc: Ensemble Learning in the Presence of Outliers, Gunnar R\344tsch, Bernhard Scholkopf, Alexander J. Smola, Klaus-Robert Muller, Takashi Onoda and Sebastian Mika [ps][pdf][djvu] Nonlinear Discriminant Analysis Using Kernel Functions, Volker Roth and Volker Steinhage [ps][pdf][djvu] An Analysis of Turbo Decoding with Gaussian Densities, Paat Rusmevichientong and Benjamin Van Roy [ps][pdf][djvu] Support Vector Method for Novelty Detection, Bernhard Scholkopf, Robert C. Williamson, Alexander J. Smola, John Shawe-Taylor and John C. Platt [ps][pdf][djvu] Better Generative Models for Sequential Data Problems: Bidirectional Recurrent Mixture Density Networks, Mike Schuster [ps][pdf][djvu] Greedy Importance Sampling, Dale Schuurmans [ps][pdf][djvu] Bayesian Model Selection for Support Vector Machines, Gaussian Processes and Other Kernel Classifiers, Matthias Seeger [ps][pdf][djvu] Leveraged Vector Machines, Yoram Singer [ps][pdf][djvu] Agglomerative Information Bottleneck, Noam Slonim and Naftali Tishby [ps][pdf][djvu] Training Data Selection for Optimal Generalization in Trigonometric Polynomial Networks, Masashi Sugiyama and Hidemitsu Ogawa [ps][pdf][djvu] Predictive App roaches for Choosing Hyperparameters in Gaussian Processes, S. Sundararajan and S. Sathiya Keerthi [ps][pdf][djvu] On Input Selection with Reversible Jump Markov Chain Monte Carlo Sampling, Peter Sykacek [ps][pdf][djvu] Building Predictive Models from Fractal Representations of Symbolic Sequences, Peter Tino and Georg Dorffner [ps][pdf][djvu] The Relevance Vector Machine, Michael E. Tipping [ps][pdf][djvu] Support Vector Method for Multivariate Density Estimation, Vladimir N. Vapnik and Sayan Mukherjee [ps][pdf][djvu] Dual Estimation and the Unscented Transformation, Eric A. Wan, Rudolph van der Merwe and Alex T. Nelson [ps][pdf][djvu] Correctness of Belief Propagation in Gaussian Graphical Models of Arbitrary Topology, Yair Weiss and William T. Freeman [ps][pdf][djvu] A MCMC Approach to Hierarchical Mixture Modelling, Christopher K. I. Williams [ps][pdf][djvu] Data Visualization and Feature Selection: New Algorithms for Nongaussian Data, Howard Hua Yang and John Moody [ps][pdf][djvu] Manifold Stochastic Dynamics for Bayesian Learning, Mark Ziochin and Yoram Baram [ps][pdf][djvu] The Parallel Problems Server: an Interactive Tool for Large Scale Machine Learning, Charles Lee Isbell, Jr. and Parry Husbands [ps][pdf][djvu] An Oculo-Motor System with Multi-Chip Neuromorphic Analog VLSI Control, Oliver Landolt and Steve Gyger [ps][pdf][djvu] A Winner-Take-All Circuit with Controllable Soft Max Property, Shih-Chii Liu. [ps][pdf][djvu] A Neuromorphic VLSI System for Modeling the Neural Control of Axial Locomotion, Girish N. Patel, Edgar A. Brown and Stephen P. DeWeerth [ps][pdf][djvu] Bifurcation Analysis of a Silicon Neuron, Girish N. Patel, Gennady S. Cymbalyuk, Ronald L. Calabrese and Stephen P. DeWeerth [ps][pdf][djvu] An Analog VLSI Model of Periodicity Extraction, Andre van Schaik [ps][pdf][djvu] An Oscillatory Correlation Frame work for Computational Auditory Scene Analysis, Guy J. Brown and DeLiang L. Wang [ps][pdf][djvu] Bayesian Modelling of fMRI lime Series, Pedro A. d. F. R. Hojen-S\370rensen, Lars Kai Hansen and Carl Edward Rasmussen [ps][pdf][djvu] Neural System Model of Human Sound Localization, Craig T. Jin and Simon Carlile [ps][pdf][djvu] Spectral Cues in Human Sound Localization, Craig T. Jin, Anna Corderoy, Simon Carlile and Andre van Schaik [ps][pdf][djvu] Broadband Direction-Of-Arrival Estimation Based on Second Order Statistics, Justinian Rosca, Joseph O Ruanaidh, Alexander Jourjine and Scott Rickard [ps][pdf][djvu] Constrained Hidden Markov Models, Sam Roweis [ps][pdf][djvu] Online Independent Component Analysis with Local Learning Rate Adaptation, Nicol N. Schraudolph and Xavier Giannakopoulos [ps][pdf][djvu] Speech Modelling Using Subspace and EM Techniques, Gavin Smith, Joao F. G. de Freitas, Tony Robinson and Mahesan Niranjan [ps][pdf][djvu] Search for Information Bearing Components in Speech, Howard Hua Yang and Hynek Hermansky [ps][pdf][djvu] Audio Vision: Using Audio-Visual Synchrony to Locate Sounds, John Hershey and Javier R. Movellan [ps][pdf][djvu] Bayesian Reconstruction of 3D Human Motion from Single-Camera Video, Nicholas R. Howe, Michael E. Leventon and William T. Freeman [ps][pdf][djvu] Emergence of Topography and Complex Cell Properties from Natural Images using Extensions of ICA, Aapo Hyvarinen and Patrik Hoyer [ps][pdf][djvu] An Information-Theoretic Framework for Understanding Saccadic Eye Movements, Tai Sing Lee and Stella X. Yu [ps][pdf][djvu] Learning Sparse Codes with a Mixture-of-Gaussians Prior, Bruno A. Olshausen and K. Jarrod Millman [ps][pdf][djvu] Hierarchical Image Probability (H1P) Models, Clay D. Spence and Lucas Parra [ps][pdf][djvu] Scale Mixtures of Gaussians and the Statistics of Natural Images, Martin J. Wainwright and Eero P. Simoncelli [ps][pdf][djvu] A SNoW-Based Face Detector, Ming-Hsuan Yang, Dan Roth and Narendra Ahuja [ps][pdf][djvu] Managing Uncertainty in Cue Combination, Zhiyong Yang and Richard S. Zemel [ps][pdf][djvu] Robust Learning of Chaotic Attractors, Rembrandt Bakker, Jaap C. Schouten, Marc-Olivier Coppens, Floris Takens, C. Lee Giles and Cor M. van den Bleek [ps][pdf][djvu] Image Representations for Facial Expression Coding, Marian Stewart Bartlett, Gianluca Donato, Javier R. Movellan, Joseph C. Hager, Paul Ekman and Terrence J. Sejnowski [ps][pdf][djvu] Low Power Wireless Communication via Reinforcement Learning, Timothy X. Brown [ps][pdf][djvu] Learning Informative Statistics: A Nonparametnic Approach, John W. Fisher III, Alexander T. Ihier and Paul A. Viola [ps][pdf][djvu] Kirchoff Law Markov Fields for Analog Circuit Design, Richard M. Golden [ps][pdf][djvu] Learning the Similarity of Documents: An Information-Geometric Approach to Document Retrieval and Categorization, Thomas Hofmann [ps][pdf][djvu] Constructing Heterogeneous Committees Using Input Feature Grouping: Application to Economic Forecasting, Yuansong Liao and John Moody [ps][pdf][djvu] 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 [ps][pdf][djvu] Churn Reduction in the Wireless Industry, Michael C. Mozer, Richard Wolniewicz, David B. Grimes, Eric Johnson and Howard Kaushansky [ps][pdf][djvu] Unmixing Hyperspectral Data, Lucas Parra, Clay D. Spence, Paul Sajda, Andreas Ziehe and Klaus-Robert Muller [ps][pdf][djvu] Application of Blind Separation of Sources to Optical Recording of Brain Activity, Holger Schoner, Martin Stetter, Ingo SchieBi, John E.W. Mayhew, Jennifer Lund, Niall McLoughlin and Klaus Obermayer [ps][pdf][djvu] Reinforcement Learning for Spoken Dialogue Systems, Satinder Singh, Michael Kearns, Diane Litman and Marilyn Walker [ps][pdf][djvu] Image Recognition in Context: Application to Microscopic Urinalysis, Xubo B. Song, Joseph Sill, Yaser Abu-Mostafa and Harvey Kasdan [ps][pdf][djvu] Generalized Model Selection for Unsupervised Learning in High Dimensions, Shivakumar Vaithyanathan and Byron Dom [ps][pdf][djvu] Learning from User Feedback in Image Retrieval Systems, Nuno Vasconcelos and Andrew Lippman [ps][pdf][djvu] An Environment Model for Nonstationary Reinforcement Learning, Samuel P. M. Choi, Dit-Yan Yeung and Nevin L. Zhang [ps][pdf][djvu] State Abstraction in MAXQ Hierarchical Reinforcement Learning, Thomas G. Dietterich [ps][pdf][djvu] Approximate Planning in Large POMDPs via Reusable Trajectories, Michael Kearns, Yishay Mansour and Andrew Y. Ng [ps][pdf][djvu] Actor-Critic Algorithms, Vijay R. Konda and John N. Tsitsiklis [ps][pdf][djvu] Bayesian Map Learning in Dynamic Environments, Kevin P. Murphy [ps][pdf][djvu] Policy Search via Density Estimation, Andrew Y. Ng, Ronald Parr and Daphne Koller [ps][pdf][djvu] Neural Network Based Model Predictive Control, Stephen Piche, Jim Keeler, Greg Martin, Gene Boe, Doug Johnson and Mark Gerules [ps][pdf][djvu] Reinforcement Learning Using Approximate Belief States, Andr\351s Rodriguez, Ronald Parr and Daphne Koller [ps][pdf][djvu] Coastal Navigation with Mobile Robots, Nicholas Roy and Sebastian Thrun [ps][pdf][djvu] Learning Factored Representations for Partially Observable Markov Decision Processes, Brian Sallans [ps][pdf][djvu] Policy Gradient Methods for Reinforcement Learning with Function Approximation, Richard S. Sutton, David McAllester, Satinder Singh and Yishay Mansour [ps][pdf][djvu] Monte Carlo POMDPs, Sebastian Thrun [ps][pdf][djvu] Index of Authors [ps][pdf][djvu] Keyword Index [ps][pdf][djvu] |