NIPS 2000: Denver, CO, USA
Todd K. Leen, Thomas G. Dietterich, Volker Tresp (Eds.): Advances in Neural Information Processing Systems 13, Papers from Neural Information Processing Systems (NIPS) 2000, Denver, CO, USA. MIT Press 2001- Ranit Aharonov-Barki, Isaac Meilijson, Eytan Ruppin: Who Does What? A Novel Algorithm to Determine Function Localization. 3-9
- Shimon Edelman, Nathan Intrator: A Productive, Systematic Framework for the Representation of Visual Structure. 10-16
- David B. Grimes, Michael Mozer: The Interplay of Symbolic and Subsymbolic Processes in Anagram Problem Solving. 17-23
- Szabolcs Káli, Peter Dayan: Hippocampally-Dependent Consolidation in a Hierarchical Model of Neocortex. 24-30
- In Jae Myung, Mark A. Pitt, Shaobo Zhang, Vijay Balasubramanian: The Use of MDL to Select among Computational Models of Cognition. 38-44
- Bosco S. Tjan: Adaptive Object Representation with Hierarchically-Distributed Memory Sites. 66-72
- Blaise Agüera y Arcas, Adrienne L. Fairhall, William Bialek: What Can a Single Neuron Compute? 75-81
- Kevin A. Archie, Bartlett W. Mel: Dendritic Compartmentalization Could Underlie Competition and Attentional Biasing of Simultaneous Visual Stimuli. 82-88
- Angelo Arleo, Fabrizio Smeraldi, Stéphane Hug, Wulfram Gerstner: Place Cells and Spatial Navigation Based on 2D Visual Feature Extraction, Path Integration, and Reinforcement Learning. 89-95
- William Bialek: Stability and Noise in Biochemical Switches. 103-109
- Gal Chechik, Naftali Tishby: Temporally Dependent Plasticity: An Information Theoretic Account. 110-116
- Sophie Denève, Jean-René Duhamel, Alexandre Pouget: A New Model of Spatial Representation in Multimodal Brain Areas. 117-123
- Adrienne L. Fairhall, Geoffrey D. Lewen, William Bialek, Robert R. de Ruyter van Steveninck: Multiple Timescales of Adaptation in a Neural Code. 124-130
- Thomas Natschläger, Wolfgang Maass, Eduardo D. Sontag, Anthony M. Zador: Processing of Time Series by Neural Circuits with Biologically Realistic Synaptic Dynamics. 145-151
- Silvia Scarpetta, Zhaoping Li, John A. Hertz: Spike-Timing-Dependent Learning for Oscillatory Networks. 152-158
- Elad Schneidman, Naama Brenner, Naftali Tishby, Robert R. de Ruyter van Steveninck, William Bialek: Universality and Individuality in a Neural Code. 159-165
- Odelia Schwartz, Eero P. Simoncelli: Natural Sound Statistics and Divisive Normalization in the Auditory System. 166-172
- Mario F. Simoni, Gennady S. Cymbalyuk, Michael E. Sorensen, Ronald L. Calabrese, Stephen P. DeWeerth: Development of Hybrid Systems: Interfacing a Silicon Neuron to a Leech Heart Interneuron. 173-179
- Carl van Vreeswijk: Whence Sparseness? 180-186
- Peter Dayan: Competition and Arbors in Ocular Dominance. 203-209
- Richard H. R. Hahnloser, H. Sebastian Seung: Permitted and Forbidden Sets in Symmetric Threshold-Linear Networks. 217-223
- Ralf Herbrich, Thore Graepel: A PAC-Bayesian Margin Bound for Linear Classifiers: Why SVMs work. 224-230
- Vladimir Koltchinskii, Dmitriy Panchenko, Fernando Lozano: Some New Bounds on the Generalization Error of Combined Classifiers. 245-251
- Adam Kowalczyk: Sparsity of Data Representation of Optimal Kernel Machine and Leave-one-out Estimator. 252-258
- Robert A. Legenstein, Wolfgang Maass: Foundations for a Circuit Complexity Theory of Sensory Processing. 259-265
- Dörthe Malzahn, Manfred Opper: Learning Curves for Gaussian Processes Regression: A Framework for Good Approximations. 273-279
- Ilya Nemenman, William Bialek: Learning Continuous Distributions: Simulations With Field Theoretic Priors. 287-293
- Bernhard Schölkopf: The Kernel Trick for Distances. 301-307
- Alex J. Smola, Zoltán L. Óvári, Robert C. Williamson: Regularization with Dot-Product Kernels. 308-314
- Toshiyuki Tanaka: Analysis of Bit Error Probability of Direct-Sequence CDMA Multiuser Demodulators. 315-321
- Renato Vicente, David Saad, Yoshiyuki Kabashima: Error-correcting Codes on a Bethe-like Lattice. 322-328
- Sumio Watanabe: Algebraic Information Geometry for Learning Machines with Singularities. 329-335
- Ole Winther: Computing with Finite and Infinite Networks. 336-342
- K. Y. Michael Wong, Hidetoshi Nishimori: Stagewise Processing in Error-correcting Codes and Image Restoration. 343-349
- Xiaohui Xie, Richard H. R. Hahnloser, H. Sebastian Seung: Learning Winner-take-all Competition Between Groups of Neurons in Lateral Inhibitory Networks. 350-356
- Tong Zhang: Convergence of Large Margin Separable Linear Classification. 357-363
- Asa Ben-Hur, David Horn, Hava T. Siegelmann, Vladimir Vapnik: A Support Vector Method for Clustering. 367-373
- Chiranjib Bhattacharyya, S. Sathiya Keerthi: A Variational Mean-Field Theory for Sigmoidal Belief Networks. 374-380
- Timothy X. Brown: Direct Classification with Indirect Data. 381-387
- Rich Caruana, Steve Lawrence, C. Lee Giles: Overfitting in Neural Nets: Backpropagation, Conjugate Gradient, and Early Stopping. 402-408
- Gert Cauwenberghs, Tomaso Poggio: Incremental and Decremental Support Vector Machine Learning. 409-415
- David A. Cohn, Thomas Hofmann: The Missing Link - A Probabilistic Model of Document Content and Hypertext Connectivity. 430-436
- Koby Crammer, Yoram Singer: Improved Output Coding for Classification Using Continuous Relaxation. 437-443
- Carlotta Domeniconi, Jing Peng, Dimitrios Gunopulos: An Adaptive Metric Machine for Pattern Classification. 458-464
- Oliver B. Downs: High-temperature Expansions for Learning Models of Nonnegative Data. 465-471
- Charles Dugas, Yoshua Bengio, François Bélisle, Claude Nadeau, René Garcia: Incorporating Second-Order Functional Knowledge for Better Option Pricing. 472-478
- Gal Elidan, Noam Lotner, Nir Friedman, Daphne Koller: Discovering Hidden Variables: A Structure-Based Approach. 479-485
- Brendan J. Frey, Anitha Kannan: Accumulator Networks: Suitors of Local Probability Propagation. 486-492
- Brendan J. Frey, Relu Patrascu, Tommi Jaakkola, Jodi Moran: Sequentially Fitting ``Inclusive'' Trees for Inference in Noisy-OR Networks. 493-499
- Claudio Gentile: A New Approximate Maximal Margin Classification Algorithm. 500-506
- Zoubin Ghahramani, Matthew J. Beal: Propagation Algorithms for Variational Bayesian Learning. 507-513
- Sepp Hochreiter, Michael Mozer: Beyond Maximum Likelihood and Density Estimation: A Sample-Based Criterion for Unsupervised Learning of Complex Models. 535-541
- Pedro A. d. F. R. Højen-Sørensen, Ole Winther, Lars Kai Hansen: Ensemble Learning and Linear Response Theory for ICA. 542-548
- Ulrik Kjems, Lars Kai Hansen, Stephen C. Strother: Generalizable Singular Value Decomposition for Ill-posed Datasets. 549-555
- Huma Lodhi, John Shawe-Taylor, Nello Cristianini, Christopher J. C. H. Watkins: Text Classification using String Kernels. 563-569
- Rudolph van der Merwe, Arnaud Doucet, Nando de Freitas, Eric A. Wan: The Unscented Particle Filter. 584-590
- Sebastian Mika, Gunnar Rätsch, Klaus-Robert Müller: A Mathematical Programming Approach to the Kernel Fisher Algorithm. 591-597
- Thomas P. Minka: Automatic Choice of Dimensionality for PCA. 598-604
- Eiji Mizutani, James Demmel: On Iterative Krylov-Dogleg Trust-Region Steps for Solving Neural Networks Nonlinear Least Squares Problems. 605-611
- Oren Shriki, Haim Sompolinsky, Daniel D. Lee: An Information Maximization Approach to Overcomplete and Recurrent Representations. 612-618
- Michael E. Tipping: Sparse Kernel Principal Component Analysis. 633-639
- Naftali Tishby, Noam Slonim: Data Clustering by Markovian Relaxation and the Information Bottleneck Method. 640-646
- Volker Tresp: Mixtures of Gaussian Processes. 654-660
- Martin J. Wainwright, Erik B. Sudderth, Alan S. Willsky: Tree-Based Modeling and Estimation of Gaussian Processes on Graphs with Cycles. 661-667
- Jason Weston, Sayan Mukherjee, Olivier Chapelle, Massimiliano Pontil, Tomaso Poggio, Vladimir Vapnik: Feature Selection for SVMs. 668-674
- Christopher K. I. Williams: On a Connection between Kernel PCA and Metric Multidimensional Scaling. 675-681
- Christopher K. I. Williams, Matthias Seeger: Using the Nyström Method to Speed Up Kernel Machines. 682-688
- Richard S. Zemel, Toniann Pitassi: A Gradient-Based Boosting Algorithm for Regression Problems. 696-702
- Tong Zhang: Regularized Winnow Methods. 703-709
- Hiroyuki Kurino, M. Nakagawa, Kang Wook Lee, Tomonori Nakamura, Yuusuke Yamada, Ki Tae Park, Mitsumasa Koyanagi: Smart Vision Chip Fabricated Using Three Dimensional Integration Technology. 720-726
- Fernando Pérez-Cruz, Pedro Luis Alarcón-Diana, Angel Navia-Vázquez, Antonio Artés-Rodríguez: Fast Training of Support Vector Classifiers. 734-740
- Susanne Still, Bernhard Schölkopf, Klaus Hepp, Rodney J. Douglas: Four-legged Walking Gait Control Using a Neuromorphic Chip Interfaced to a Support Vector Learning Algorithm. 741-747
- Hervé Bourlard, Samy Bengio, Katrin Weber: New Approaches Towards Robust, Adaptive Speech Recognition (invited paper). 751-757
- Hagai Attias, John C. Platt, Alex Acero, Li Deng: Speech Denoising and Dereverberation Using Probabilistic Models. 758-764
- Un-Min Bae, Soo-Young Lee: Combining ICA and Top-Down Attention for Robust Speech Recognition. 765-771
- John W. Fisher III, Trevor Darrell, William T. Freeman, Paul A. Viola: Learning Joint Statistical Models for Audio-Visual Fusion and Segregation. 772-778
- Mark J. F. Gales: Factored Semi-Tied Covariance Matrices. 779-785
- Lucas C. Parra, Clay Spence, Paul Sajda: Higher-Order Statistical Properties Arising from the Non-Stationarity of Natural Signals. 786-792
- Sam T. Roweis: One Microphone Source Separation. 793-799
- George Saon, Mukund Padmanabhan: Minimum Bayes Error Feature Selection for Continuous Speech Recognition. 800-806
- Lawrence K. Saul, Jont B. Allen: Periodic Component Analysis: An Eigenvalue Method for Representing Periodic Structure in Speech. 807-813
- Malcolm Slaney, Michele Covell: FaceSync: A Linear Operator for Measuring Synchronization of Video Facial Images and Audio Tracks. 814-820
- Jürgen Tchorz, Michael Kleinschmidt, Birger Kollmeier: Noise Suppression Based on Neurophysiologically-motivated SNR Estimation for Robust Speech Recognition. 821-827
- Serge Belongie, Jitendra Malik, Jan Puzicha: Shape Context: A New Descriptor for Shape Matching and Object Recognition. 831-837
- Rafal Bogacz, Malcolm W. Brown, Christophe G. Giraud-Carrier: Emergence of Movement Sensitive Neurons' Properties by Learning a Sparse Code for Natural Moving Images. 838-844
- James M. Coughlan, Alan L. Yuille: The Manhattan World Assumption: Regularities in Scene Statistics which Enable Bayesian Inference. 845-851
- Frank Dellaert, Steven M. Seitz, Sebastian Thrun, Charles E. Thorpe: Feature Correspondence: A Markov Chain Monte Carlo Approach. 852-858
- Trausti T. Kristjansson, Brendan J. Frey: Keeping Flexible Active Contours on Track using Metropolis Updates. 859-865
- Te-Won Lee, Thomas Wachtler, Terrence J. Sejnowski: Color Opponency Constitutes a Sparse Representation for the Chromatic Structure of Natural Scenes. 866-872
- Javier R. Movellan, Paul Mineiro, Ruth J. Williams: Partially Observable SDE Models for Image Sequence Recognition Tasks. 880-886
- Bruno A. Olshausen, Phil Sallee, Michael S. Lewicki: Learning Sparse Image Codes using a Wavelet Pyramid Architecture. 887-893
- Dirk Ormoneit, Hedvig Sidenbladh, Michael J. Black, Trevor Hastie: Learning and Tracking Cyclic Human Motion. 894-900
- Penio S. Penev: Redundancy and Dimensionality Reduction in Sparse-Distributed Representations of Natural Objects in Terms of Their Local Features. 901-907
- Yee Whye Teh, Geoffrey E. Hinton: Rate-coded Restricted Boltzmann Machines for Face Recognition. 908-914
- Barbara Zenger, Christof Koch: Divisive and Subtractive Mask Effects: Linking Psychophysics and Biophysics. 915-921
- Michael S. Gray, Terrence J. Sejnowski, Javier R. Movellan: A Comparison of Image Processing Techniques for Visual Speech Recognition Applications. 939-945
- Paul M. Hayton, Bernhard Schölkopf, Lionel Tarassenko, Paul Anuzis: Support Vector Novelty Detection Applied to Jet Engine Vibration Spectra. 946-952
- Guy Mayraz, Geoffrey E. Hinton: Recognizing Hand-written Digits Using Hierarchical Products of Experts. 953-959
- Predrag Neskovic, Philip C. Davis, Leon N. Cooper: Interactive Parts Model: An Application to Recognition of On-line Cursive Script. 974-980
- Vladimir Pavlovic, James M. Rehg, John MacCormick: Learning Switching Linear Models of Human Motion. 981-987
- Liam Pedersen, Dimitrios Apostolopoulos, William Whittaker: Bayes Networks on Ice: Robotic Search for Antarctic Meteorites. 988-994
- Jakob Carlström: Decomposition of Reinforcement Learning for Admission Control of Self-Similar Call Arrival Processes. 1033-1039
- Geoffrey J. Gordon: Reinforcement Learning with Function Approximation Converges to a Region. 1040-1046
- Natalia Hernandez-Gardiol, Sridhar Mahadevan: Hierarchical Memory-Based Reinforcement Learning. 1047-1053
- Anders Jonsson, Andrew G. Barto: Automated State Abstraction for Options using the U-Tree Algorithm. 1054-1060
- Dirk Ormoneit, Peter W. Glynn: Kernel-Based Reinforcement Learning in Average-Cost Problems: An Application to Optimal Portfolio Choice. 1068-1074
- Brian Sallans, Geoffrey E. Hinton: Using Free Energies to Represent Q-values in a Multiagent Reinforcement Learning Task. 1075-1081
- Christian R. Shelton: Balancing Multiple Sources of Reward in Reinforcement Learning. 1082-1088
- Robert St-Aubin, Jesse Hoey, Craig Boutilier: APRICODD: Approximate Policy Construction Using Decision Diagrams. 1089-1095
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last updated on 2013-06-18T211851 by the dblp team