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NIPS*1998
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| Title Pages [ps][pdf][djvu] Evidence for a Forward Dynamics Model in Human Adaptive Motor Control, Nikhil Bhushan and Reza Shadmehr [ps][pdf][djvu] Perceiving without Learning: From Spirals to Inside/Outside Relations, Ke Chen and DeLiang L. Wang [ps][pdf][djvu] A Model for Associative Multiplication, G. Bjorn Christianson and Suzanna Becker [ps][pdf][djvu] Facial Memory Is Kernel Density Estimation (Almost), Matthew N. Dailey, Garrison W. Cottrell and Thomas A. Busey [ps][pdf][djvu] Multiple Paired Forward-Inverse Models for Human Motor Learning and Control, Masahiko Haruno, Daniel M. Wolpert and Mitsuo Kawato [ps][pdf][djvu] Utilizing lime: Asynchronous Binding, Bradley C. Love [ps][pdf][djvu] Mechanisms of Generalization in Perceptual Learning, Zili Liu and Daphna Weinshall [ps][pdf][djvu] A Principle for Unsupervised Hierarchical Decomposition of Visual Scenes, Michael C. Mozer [ps][pdf][djvu] Bayesian Modeling of Human Concept Learning, Joshua B. Tenenbaum [ps][pdf][djvu] Temporally Asymmetric Hebbian Learning, Spike liming and Neural Response Variability, L. F. Abbott and Sen Song [ps][pdf][djvu] Contrast Adaptation in Simple Cells by Changing the Transmitter Release Probability, Peter Adorjan and Klaus Obermayer [ps][pdf][djvu] Where Does the Population Vector of Motor Cortical Cells Point during Reaching Movements?, Pierre Baraduc, Emmanuel Guigon and Yves Burnod [ps][pdf][djvu] Recurrent Cortical Amplification Produces Complex Cell Responses, Frances S. Chance, Sacha B. Nelson and L. F. Abbott [ps][pdf][djvu] Neuronal Regulation Implements Efficient Synaptic Pruning, Gal Chechik, Isaac Meilijson and Eytan Ruppin [ps][pdf][djvu] Divisive Normalization, Line Attractor Networks and Ideal Observers, Sophie Deneve, Alexandre Pouget and Peter E. Latham [ps][pdf][djvu] Synergy and Redundancy among Brain Cells of Behaving Monkeys, Itay Gat and Naftali Tishby [ps][pdf][djvu] Analyzing and Visualizing Single-Trial Event-Related Potentials, Tzyy-Ping Jung, Scott Makeig, Marissa Westerfield, Jeanne Townsend, Eric Courchesne and Terrence J. Sejnowski [ps][pdf][djvu] Spike-Based Compared to Rate-Based Hebbian Learning, Richard Kempter, Wuifram Gerstner and J. Leo van Hemmen [ps][pdf][djvu] Signal Detection in Noisy Weakly-Active Dendrites, Amit Manwani and Christof Koch [ps][pdf][djvu] The Role of Lateral Cortical Competition in Ocular Dominance Development, Christian Piepenbrock and Klaus Obermayer [ps][pdf][djvu] Multi-Electrode Spike Sorting by Clustering Transfer Functions, Dmitry Rinberg, Hanan Davidowitz and Naftali Tishby [ps][pdf][djvu] Modeling Surround Suppression in V1 Neurons with a Statistically Derived Normalization Model, Eero P. Simoncelli and Odelia Schwartz [ps][pdf][djvu] Information Maximization in Single Neurons, Martin Stemmler and Christof Koch [ps][pdf][djvu] The Effect of Correlations on the Fisher Information of Population Codes, Hyoungsoo Yoon and Haim Sompolinsky [ps][pdf][djvu] Distributional Population Codes and Multiple Motion Models, Richard S. Zemel and Peter Dayan [ps][pdf][djvu] Tractable Variational Structures for Approximating Graphical Models, David Barber and Wim Wiegerinck [ps][pdf][djvu] Almost Linear VC Dimension Bounds for Piecewise Polynomial Networks, Peter L. Bartlett, Vitaly Maiorov and Ron Meir [ps][pdf][djvu] Dynamics of Supervised Learning with Restricted Training Sets, A. C. C. Coolen and David Saad [ps][pdf][djvu] Dynamically Adapting Kernels in Support Vector Machines, Nello Cristianini, Cohn Campbell and John Shawe-Taylor [ps][pdf][djvu] Phase Diagram and Storage Capacity of Sequence-Storing Neural Networks, A. During, A. C. C. Coolen and D. Sherrington [ps][pdf][djvu] Finite-Dimensional Approximation of Gaussian Processes, Giancarlo Ferrari-Trecate, Christopher K. I. Williams and Manfred Opper [ps][pdf][djvu] Linear Hinge Loss and Average Margin, Claudio Gentile and Manfred K. Warmuth [ps][pdf][djvu] Unsupervised and Supervised Clustering: The Mutual Information between Parameters and Observations, Didier Herschkowitz and Jean-Pierre Nadal [ps][pdf][djvu] Convergence of the Wake-Sleep Algorithm, Shiro Ikeda, Shun-ichi Amari and Hiroyuki Nakahara [ps][pdf][djvu] The Belief in TAP, Yoshiyuki Kabashima and David Saad [ps][pdf][djvu] Optimizing Classifers for Imbalanced Training Sets, Grigoris Karakoulas and John Shawe-Taylor [ps][pdf][djvu] Inference in Multilayer Networks via Large Deviation Bounds, Michael Kearns and Lawrence Saul [ps][pdf][djvu] Stationarity and Stability of Autoregressive Neural Network Processes, Friedrich Leisch, Adrian Trapletti and Kurt Hornik [ps][pdf][djvu] Computational Differences between Asymmetrical and Symmetrical Networks, Zhaoping Li and Peter Dayan [ps][pdf][djvu] A Precise Characterization of the Class of Languages Recognized by Neural Nets under Gaussian and Other Common Noise Distributions Wolfgang Maass and Eduardo D. Sontag [ps][pdf][djvu] Direct Optimization of Margins Improves Generalization in Combined Classifiers, Llew Mason, Peter L. Bartlett and Jonathan Baxter [ps][pdf][djvu] On the Optimality of Incremental Neural Network Algorithms, Ron Meir and Vitaly Maiorov [ps][pdf][djvu] General Bounds on Bayes Errors for Regression with Gaussian Processes, Manfred Upper and Francesco Vivarelli [ps][pdf][djvu] Mean Field Methods for Classification with Gaussian Processes, Manfred Upper and Ole Winther [ps][pdf][djvu] On-Line Learning with Restricted Training Sets: Exact Solution as Benchmark for General Theories, H. C. Rae, Peter Sollich and A. C. C. Coolen [ps][pdf][djvu] Tight Bounds for the VC-Dimension of Piecewise Polynomial Networks, Akito Sakurai [ps][pdf][djvu] Shrinking the Tube: A New Support Vector Regression Algorithm, Bernhard Scholkopf, Peter L. Bartlett, Alex J. Smola and Robert Williamson [ps][pdf][djvu] Discontinuous Recall Transitions Induced by Competition Between Short- and Long-Range Interactions in Recurrent Networks, N. S. Skantzos, C. F. Beckmann and A. C. C. Coolen [ps][pdf][djvu] Learning Curves for Gaussian Processes, Peter Sollich [ps][pdf][djvu] A Theory of Mean Field Approximation, Toshiyuki Tanaka [ps][pdf][djvu] Learning a Hierarchical Belief Network of Independent Factor Analyzers, Hagai Attias [ps][pdf][djvu] Semi-Supervised Support Vector Machines, Kristin Bennett and Ayhan Demiriz [ps][pdf][djvu] Lazy Learning Meets the Recursive Least Squares Algorithm, Mauro Birattari, Gianluca Bontempi and Hugues Bersini [ps][pdf][djvu] Bayesian PCA, Christopher M. Bishop [ps][pdf][djvu] Learning Multi-Class Dynamics, Andrew Blake, Ben North and Michael Isard [ps][pdf][djvu] Approximate Learning of Dynamic Models, Xavier Boyen and Daphne Koller [ps][pdf][djvu] Fisher Scoring and a Mixture of Modes Approach for Approximate Inference and Learning in Nonlinear State Space Models, Thomas Briegel and Volker Tresp [ps][pdf][djvu] Global Optimisation of Neural Network Models via Sequential Sampling, Joao F. G. de Freitas, Mahesan Niranjan, Arnaud Doucet and Andrew H. Gee [ps][pdf][djvu] Efficient Bayesian Parameter Estimation in Large Discrete Domains, Nir Friedman and Yoram Singer [ps][pdf][djvu] A Randomized Algorithm for Pairwise Clustering, Yoram Gdalyahu, Daphna Weinshall and Michael Werman [ps][pdf][djvu] Learning Nonlinear Dynamical Systems Using an EM Algorithm, Zoubin Ghahramani and Sam T. Roweis [ps][pdf][djvu] Classification on Pairwise Proximity Data, Thore Graepel, Ralf Herbrich, Peter Bollmann-Sdorra and Klaus Obermayer [ps][pdf][djvu] Outcomes of the Equivalence of Adaptive Ridge with Least Absolute Shrinkage, Yves Grandvalet and Stephane Canu [ps][pdf][djvu] Visualizing Group Structure, Marcus Held, Jan Puzicha and Joachim M. Buhmann [ps][pdf][djvu] Source Separation as a By-Product of Regularization, Sepp Hochreiter and Jurgen Schmidhuber [ps][pdf][djvu] Learning from Dyadic Data, Thomas Hofmann, Jan Puzicha and Michael I. Jordan [ps][pdf][djvu] Sparse Code Shrinkage: Denoising by Nonlinear Maximum Likelihood Estimation, Aapo Hyvarinen, Patrik Hoyer and Erkki Oja [ps][pdf][djvu] Restructuring Sparse High Dimensional Data for Effective Retrieval, Charles Lee Isbell, Jr. and Paul Viola [ps][pdf][djvu] Exploiting Generative Models in Discriminative Classifiers, Tommi S. Jaakkola and David Haussler [ps][pdf][djvu] Maximum Conditional Likelihood via Bound Maximization and the CEM Algorithm, Tony Jebara and Alex Pentland [ps][pdf][djvu] A Polygonal Line Algorithm for Constructing Principal Curves, Balazs Kegl, Adam Krzyzak, Tamas Linder and Kenneth Zeger [ps][pdf][djvu] Unsupervised Classification with Non-Gaussian Mixture Models Using ICA, Te-Won Lee, Michael S. Lewicki and Terrence J. Sejnowski [ps][pdf][djvu] Learning a Continuous Hidden Variable Model for Binary Data, Daniel D. Lee and Haim Sompolinsky [ps][pdf][djvu] Neural Networks for Density Estimation, Malik Magdon-Ismail and Amir Atiya [ps][pdf][djvu] Exploratory Data Analysis Using Radial Basis Function Latent Variable Models, Alan D. Marrs and Andrew R. Webb [ps][pdf][djvu] Kernel PCA and De-Noising in Feature Spaces, Sebastian Mika, Bernhard Scholkopf, Alex J. Smola, Klaus-Robert Muller, Matthias Scholz and Gunnar Ratsch [ps][pdf][djvu] Very Fast EM-Based Mixture Model Clustering Using Multiresolution Kd-Trees, Andrew W. Moore [ps][pdf][djvu] Replicator Equations, Maximal Cliques, and Graph Isomorphism, Marcello Pelillo [ps][pdf][djvu] Using Analytic QP and Sparseness to Speed Training of Support Vector Machines, John C. Platt [ps][pdf][djvu] Regularizing AdaBoost, Gunnar Ratsch, Takashi Onoda and Klaus-Robert Muller [ps][pdf][djvu] Boxlets: A Fast Convolution Algorithm for Signal Processing and Neural Networks, Patrice Y. Simard, Leon Bottou, Patrick Haffner and Yann Le Cun [ps][pdf][djvu] Batch and On-Line Parameter Estimation of Gaussian Mixtures Based on the Joint Entropy, Yoram Singer and Manfred K. Warmuth [ps][pdf][djvu] Semiparametric Support Vector and Linear Programming Machines, Alex J. Smola, Thilo T. Frieß and Bernhard Scholkopf [ps][pdf][djvu] Probabilistic Visualisation of High-Dimensional Binary Data, Michael E. Tipping [ps][pdf][djvu] SMEM Algorithm for Mixture Models, Naonori Ueda, Ryohei Nakano, Zoubin Ghabramani and Geoffrey E. Hinton [ps][pdf][djvu] Learning Mixture Hierarchies, Nuno Vasconcelos and Andrew Lippman [ps][pdf][djvu] Discovering Hidden Features with Gaussian Processes Regression, Francesco Vivarelli and Christopher K. I. Williams [ps][pdf][djvu] The Bias-Variance Tradeoff and the Randomized GACV, Grace Wahba, Xiwu Lin, Fangyu Gao, Dong Xiang, Ronald Klein and Barbara Klein [ps][pdf][djvu] Basis Selection for Wavelet Regression, Kevin R. Wheeler and Atam P. Dhawan [ps][pdf][djvu] DTs: Dynamic Trees, Christopher K. I. Williams and Nicholas J. Adams [ps][pdf][djvu] Convergence Rates of Algorithms for Visual Search: Detecting Visual Contours, A. L. Yuille and James M. Coughlan [ps][pdf][djvu] Blind Separation of Filtered Sources Using State-Space Approach, Liqing Zhang and Andrzej Cichocki [ps][pdf][djvu] Analog VLSI Cellular Implementation of the Boundary Contour System, Gert Cauwenberghs and James Waskiewicz [ps][pdf][djvu] Active Noise Canceling Using Analog Neuro-Chip with On-Chip Learning Capability, Jung-Wook Cho and Soo-Young Lee [ps][pdf][djvu] A Micropower CMOS Adaptive Amplitude and Shift Invariant Vector Quantiser, Richard J. Coggins, Raymond J. W. Wang and Marwan A. Jabri [ps][pdf][djvu] Optimizing Correlation Algorithms for Hardware-Based Transient Classification, R. Timothy Edwards, Gert Cauwenberghs and Fernando J. Pineda [ps][pdf][djvu] VLSI Implementation of Motion Centroid Localization for Autonomous Navigation, Ralph Etienne-Cummings, Vilctor Gruev and Mohammed Abdel Ghani [ps][pdf][djvu] A Neuromorphic Monaural Sound Localizer, John G. Harris, Chiang-Jung Pu and Jose C. Principe [ps][pdf][djvu] An Integrated Vision Sensor for the Computation of Optical Flow Singular Points, Charles M. Higgins and Christof Koch [ps][pdf][djvu] Computation of Smooth Optical Flow in a Feedback Connected Analog Network, Alan Stocker and Rodney Douglas [ps][pdf][djvu] A High Performance k-NN Classifier Using a Binary Correlation Matrix Memory, Ping Zhou, Jim Austin and John Kennedy [ps][pdf][djvu] An Entropic Estimator for Structure Discovery, Matthew Brand [ps][pdf][djvu] Coding Time-Varying Signals Using Sparse, Shift-Invariant Representations, Michael S. Lewicki and Terrence J. Sejnowski [ps][pdf][djvu] Controlling the Complexity of HMM Systems by Regularization, Christoph Neukirchen and Gerhard Rigoll [ps][pdf][djvu] Maximum-Likelihood Continuity Mapping (MALCOM): An Alternative to HMMs, David A. Nix and John E. Hogden [ps][pdf][djvu] Markov Processes on Curves for Automatic Speech Recognition, Lawrence Saul and Mazin Rahim [ps][pdf][djvu] A Phase Space Approach to Minimax Entropy Learning and the Minutemax Approximations, James M. Coughlan and A. L. Yuille [ps][pdf][djvu] Example-Based Image Synthesis of Articulated Figures, Trevor Darrell [ps][pdf][djvu] Learning to Estimate Scenes from Images, William T. Freeman and Egon C. Pasztor [ps][pdf][djvu] Learning to Find Pictures of People, Sergey loffe and David Forsyth [ps][pdf][djvu] Attentional Modulation of Human Pattern Discrimination Psychophysics Reproduced by a Quantitative Model, Laurent Itti, Jochen Braun, Dale K. Lee and Christof Koch [ps][pdf][djvu] A V1 Model of Pop Out and Asymmetty in Visual Search, Zhaoping Li [ps][pdf][djvu] Support Vector Machines Applied to Face Recognition, P. Jonathon Phillips [ps][pdf][djvu] Learning Lie Groups for Invariant Visual Perception, Rajesh P. N. Rao and Daniel L. Ruderman [ps][pdf][djvu] General-Purpose Localization of Textured Image Regions, Ruth Rosenholtz [ps][pdf][djvu] Probabilistic Image Sensor Fusion, Ravi K. Sharma, Todd K. Leen and Misha Pavel [ps][pdf][djvu] Orientation, Scale, and Discontinuity as Emergent Properties of Illusory Contour Shape, Karvel K. Thornber and Lance R. Williams [ps][pdf][djvu] Classification in Non-Metric Spaces, Daphna Weinshall, David W. Jacobs and Yoram Gdalyahu [ps][pdf][djvu] Making Templates Rotationally Invariant. An Application to Rotated Digit Recognition, Shumeet Baluja [ps][pdf][djvu] Probabilistic Modeling for Face Orientation Discrimination: Learning from Labeled and Unlabeled Data, Shumeet Baluja [ps][pdf][djvu] Adding Constrained Discontinuities to Gaussian Process Models of Wind Fields, Dan Cornford, Ian T. Nabney and Christopher K. I. Williams [ps][pdf][djvu] Vertex Identification in High Energy Physics Experiments, Gideon Dror, Halina Abramowicz and David Horn [ps][pdf][djvu] Familiarity Discrimination of Radar Pulses, Eric Granger, Stephen Grossberg, Mark A. Rubin and William W. Streilein [ps][pdf][djvu] Fast Neural Network Emulation of Dynamical Systems for Computer Animation, Radek Grzeszczuk, Demetri Terzopoulos and Geoffrey E. Hinton [ps][pdf][djvu] Call-Based Fraud Detection in Mobile Communication Networks Using a Hierarchical Regime-Switching Model, Jaakko Hollmen and Volker Tresp [ps][pdf][djvu] Graph Matching for Shape Retrieval, Benoit Huet, Andrew D. J. Cross and Edwin R. Hancock [ps][pdf][djvu] Scheduling Straight-Line Code Using Reinforcement Learning and Rollouts, Amy McGovern and Eliot Moss [ps][pdf][djvu] Bayesian Modeling of Facial Similarity, Baback Moghaddam, Tony Jebara and Alex Pentland [ps][pdf][djvu] Reinforcement Learning for Trading, John Moody and Matthew Saffell [ps][pdf][djvu] Graphical Models for Recognizing Human Interactions, Nuria M. Oliver, Barbara Rosario and Alex Pentland [ps][pdf][djvu] Independent Component Analysis of Intracellular Calcium Spike Data, Klaus Prank, Julia Borger, Alexander von zur Muhlen, Georg Brabant and Christof Schofl [ps][pdf][djvu] Applications of Multi-Resolution Neural Networks to Mammography, Clay D. Spence and Paul Sajda [ps][pdf][djvu] Robot Docking Using Mixtures of Gaussians, Matthew M. Williamson, Roderick Murray-Smith and Volker Hansen [ps][pdf][djvu] Using Collective Intelligence to Route Internet Traffic, David H. Wolpert, Kagan Turner and Jeremy Frank [ps][pdf][djvu] Robust, Efficient, Globally-Optimized Reinforcement Learning with the Parti-Game Algorithm, Mohammad A. Al-Ansari and Ronald J. Williams [ps][pdf][djvu] Gradient Descent for General Reinforcement Learning, Leemon Baird and Andrew W. Moore [ps][pdf][djvu] Non-Linear PI Control Inspired by Biological Control Systems, Lyndon J. Brown, Gregory E. Gonye and James S. Schwaber [ps][pdf][djvu] Optimizing Admission Control while Ensuring Quality of Service in Multimedia Networks via Reinforcement Learning, Timothy X. Brown, Hui Tong and Satinder Singh [ps][pdf][djvu] Viewing Classifier Systems as Model Free Learning in POMDPs, Akira Hayashi and Nobuo Suematsu [ps][pdf][djvu] Finite-Sample Convergence Rates for Q-Learning and Indirect Algorithms, Michael Kearns and Satinder Singh [ps][pdf][djvu] Exploring Unknown Environments with Real-Time Search or Reinforcement Learning, Sven Koenig [ps][pdf][djvu] The Effect of Eligibility Traces on Finding Optimal Memoryless Policies in Partially Observable Markov Decision Processes, John Loch [ps][pdf][djvu] Learning Instance-Independent Value Functions to Enhance Local Search, Robert Moll, Andrew G. Barto, Theodore J. Perkins and Richard S. Sutton [ps][pdf][djvu] Barycentric Interpolators for Continuous Space and Time Reinforcement Learning, Remi Munos and Andrew W. Moore [ps][pdf][djvu] Risk Sensitive Reinforcement Learning, Ralph Neuneier and Oliver Mihatsch [ps][pdf][djvu] Coordinate Transformation Learning of Hand Position Feedback Controller by Using Change of Position Error Norm, Eimei Oyama and Susumu Tachi [ps][pdf][djvu] Learning Macro-Actions in Reinforcement Learning, Jette Randlov [ps][pdf][djvu] Reinforcement Learning Based on On-Line EM Algorithm, Masa-aki Sato and Shin Ishii [ps][pdf][djvu] A Reinforcement Learning Algorithm in Partially Observable Environments Using Short-Term Memory, Nobuo Suematsu and Akira Hayashi [ps][pdf][djvu] Improved Switching among Temporally Abstract Actions, Richard S. Sutton, Satinder Singh, Doina Precup and Balaraman Ravindran [ps][pdf][djvu] Experimental Results on Learning Stochastic Memoryless Policies for Partially Observable Markov Decision Processes, John K. Williams and Satinder Singh [ps][pdf][djvu] Index of Authors [ps][pdf][djvu] Keyword Index [ps][pdf][djvu] |