ML Anthology

NeurIPS 2000

152 papers

`n-Body' Problems in Statistical Learning Alexander G. Gray, Andrew W. Moore
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A Comparison of Image Processing Techniques for Visual Speech Recognition Applications Michael S. Gray, Terrence J. Sejnowski, Javier R. Movellan
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A Gradient-Based Boosting Algorithm for Regression Problems Richard S. Zemel, Toniann Pitassi
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A Linear Programming Approach to Novelty Detection Colin Campbell, Kristin P. Bennett
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A Mathematical Programming Approach to the Kernel Fisher Algorithm Sebastian Mika, Gunnar Rätsch, Klaus-Robert Müller
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A Neural Probabilistic Language Model Yoshua Bengio, Réjean Ducharme, Pascal Vincent
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A New Approximate Maximal Margin Classification Algorithm Claudio Gentile
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A New Model of Spatial Representation in Multimodal Brain Areas Sophie Denève, Jean-René Duhamel, Alexandre Pouget
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A PAC-Bayesian Margin Bound for Linear Classifiers: Why SVMs Work Ralf Herbrich, Thore Graepel
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A Productive, Systematic Framework for the Representation of Visual Structure Shimon Edelman, Nathan Intrator
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A Silicon Primitive for Competitive Learning David Hsu, Miguel Figueroa, Chris Diorio
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A Support Vector Method for Clustering Asa Ben-Hur, David Horn, Hava T. Siegelmann, Vladimir Vapnik
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A Tighter Bound for Graphical Models Martijn A. R. Leisink, Hilbert J. Kappen
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A Variational Mean-Field Theory for Sigmoidal Belief Networks Chiranjib Bhattacharyya, S. Sathiya Keerthi
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Accumulator Networks: Suitors of Local Probability Propagation Brendan J. Frey, Anitha Kannan
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Active Inference in Concept Learning Jonathan D. Nelson, Javier R. Movellan
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Active Learning for Parameter Estimation in Bayesian Networks Simon Tong, Daphne Koller
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Active Support Vector Machine Classification Olvi L. Mangasarian, David R. Musicant
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Adaptive Object Representation with Hierarchically-Distributed Memory Sites Bosco S. Tjan
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Algebraic Information Geometry for Learning Machines with Singularities Sumio Watanabe
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Algorithmic Stability and Generalization Performance Olivier Bousquet, André Elisseeff
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Algorithms for Non-Negative Matrix Factorization Daniel D. Lee, H. Sebastian Seung
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An Adaptive Metric Machine for Pattern Classification Carlotta Domeniconi, Jing Peng, Dimitrios Gunopulos
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An Information Maximization Approach to Overcomplete and Recurrent Representations Oren Shriki, Haim Sompolinsky, Daniel D. Lee
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Analysis of Bit Error Probability of Direct-Sequence CDMA Multiuser Demodulators Toshiyuki Tanaka
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APRICODD: Approximate Policy Construction Using Decision Diagrams Robert St-Aubin, Jesse Hoey, Craig Boutilier
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Automated State Abstraction for Options Using the U-Tree Algorithm Anders Jonsson, Andrew G. Barto
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Automatic Choice of Dimensionality for PCA Thomas P. Minka
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Balancing Multiple Sources of Reward in Reinforcement Learning Christian R. Shelton
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Bayes Networks on Ice: Robotic Search for Antarctic Meteorites Liam Pedersen, Dimitrios Apostolopoulos, William Whittaker
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Bayesian Video Shot Segmentation Nuno Vasconcelos, Andrew Lippman
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Beyond Maximum Likelihood and Density Estimation: A Sample-Based Criterion for Unsupervised Learning of Complex Models Sepp Hochreiter, Michael Mozer
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Color Opponency Constitutes a Sparse Representation for the Chromatic Structure of Natural Scenes Te-Won Lee, Thomas Wachtler, Terrence J. Sejnowski
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Combining ICA and Top-Down Attention for Robust Speech Recognition Un-Min Bae, Soo-Young Lee
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Competition and Arbors in Ocular Dominance Peter Dayan
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Computing with Finite and Infinite Networks Ole Winther
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Constrained Independent Component Analysis Wei Lu, Jagath C. Rajapakse
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Convergence of Large Margin Separable Linear Classification Tong Zhang
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Data Clustering by Markovian Relaxation and the Information Bottleneck Method Naftali Tishby, Noam Slonim
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Decomposition of Reinforcement Learning for Admission Control of Self-Similar Call Arrival Processes Jakob Carlström
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Dendritic Compartmentalization Could Underlie Competition and Attentional Biasing of Simultaneous Visual Stimuli Kevin A. Archie, Bartlett W. Mel
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Direct Classification with Indirect Data Timothy X. Brown
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Discovering Hidden Variables: A Structure-Based Approach Gal Elidan, Noam Lotner, Nir Friedman, Daphne Koller
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Divisive and Subtractive Mask Effects: Linking Psychophysics and Biophysics Barbara Zenger, Christof Koch
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Dopamine Bonuses Sham Kakade, Peter Dayan
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Efficient Learning of Linear Perceptrons Shai Ben-David, Hans-Ulrich Simon
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Emergence of Movement Sensitive Neurons' Properties by Learning a Sparse Code for Natural Moving Images Rafal Bogacz, Malcolm W. Brown, Christophe G. Giraud-Carrier
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Ensemble Learning and Linear Response Theory for ICA Pedro A. d. F. R. Højen-Sørensen, Ole Winther, Lars Kai Hansen
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Error-Correcting Codes on a Bethe-like Lattice Renato Vicente, David Saad, Yoshiyuki Kabashima
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Exact Solutions to Time-Dependent MDPs Justin A. Boyan, Michael L. Littman
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Explaining Away in Weight Space Peter Dayan, Sham Kakade
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FaceSync: A Linear Operator for Measuring Synchronization of Video Facial Images and Audio Tracks Malcolm Slaney, Michele Covell
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Factored Semi-Tied Covariance Matrices Mark J. F. Gales
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Fast Training of Support Vector Classifiers Fernando Pérez-Cruz, Pedro Luis Alarcón-Diana, Angel Navia-Vázquez, Antonio Artés-Rodríguez
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Feature Correspondence: A Markov Chain Monte Carlo Approach Frank Dellaert, Steven M. Seitz, Sebastian Thrun, Charles E. Thorpe
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Feature Selection for SVMs Jason Weston, Sayan Mukherjee, Olivier Chapelle, Massimiliano Pontil, Tomaso Poggio, Vladimir Vapnik
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Finding the Key to a Synapse Thomas Natschläger, Wolfgang Maass
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Foundations for a Circuit Complexity Theory of Sensory Processing Robert A. Legenstein, Wolfgang Maass
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Four-Legged Walking Gait Control Using a Neuromorphic Chip Interfaced to a Support Vector Learning Algorithm Susanne Still, Bernhard Schölkopf, Klaus Hepp, Rodney J. Douglas
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From Margin to Sparsity Thore Graepel, Ralf Herbrich, Robert C. Williamson
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From Mixtures of Mixtures to Adaptive Transform Coding Cynthia Archer, Todd K. Leen
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Gaussianization Scott Saobing Chen, Ramesh A. Gopinath
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Generalizable Singular Value Decomposition for Ill-Posed Datasets Ulrik Kjems, Lars Kai Hansen, Stephen C. Strother
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Generalized Belief Propagation Jonathan S. Yedidia, William T. Freeman, Yair Weiss
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Hierarchical Memory-Based Reinforcement Learning Natalia Hernandez-Gardiol, Sridhar Mahadevan
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High-Temperature Expansions for Learning Models of Nonnegative Data Oliver B. Downs
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Higher-Order Statistical Properties Arising from the Non-Stationarity of Natural Signals Lucas C. Parra, Clay Spence, Paul Sajda
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Hippocampally-Dependent Consolidation in a Hierarchical Model of Neocortex Szabolcs Káli, Peter Dayan
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Homeostasis in a Silicon Integrate and Fire Neuron Shih-Chii Liu, Bradley A. Minch
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Improved Output Coding for Classification Using Continuous Relaxation Koby Crammer, Yoram Singer
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Incorporating Second-Order Functional Knowledge for Better Option Pricing Charles Dugas, Yoshua Bengio, François Bélisle, Claude Nadeau, René Garcia
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Incremental and Decremental Support Vector Machine Learning Gert Cauwenberghs, Tomaso Poggio
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Interactive Parts Model: An Application to Recognition of On-Line Cursive Script Predrag Neskovic, Philip C. Davis, Leon N. Cooper
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Keeping Flexible Active Contours on Track Using Metropolis Updates Trausti T. Kristjansson, Brendan J. Frey
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Kernel Expansions with Unlabeled Examples Martin Szummer, Tommi Jaakkola
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Kernel-Based Reinforcement Learning in Average-Cost Problems: An Application to Optimal Portfolio Choice Dirk Ormoneit, Peter W. Glynn
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Large Scale Bayes Point Machines Ralf Herbrich, Thore Graepel
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Learning and Tracking Cyclic Human Motion Dirk Ormoneit, Hedvig Sidenbladh, Michael J. Black, Trevor Hastie
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Learning Continuous Distributions: Simulations with Field Theoretic Priors Ilya Nemenman, William Bialek
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Learning Curves for Gaussian Processes Regression: A Framework for Good Approximations Dörthe Malzahn, Manfred Opper
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Learning Joint Statistical Models for Audio-Visual Fusion and Segregation John W. Fisher Iii, Trevor Darrell, William T. Freeman, Paul A. Viola
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Learning Segmentation by Random Walks Marina Meila, Jianbo Shi
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Learning Sparse Image Codes Using a Wavelet Pyramid Architecture Bruno A. Olshausen, Phil Sallee, Michael S. Lewicki
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Learning Switching Linear Models of Human Motion Vladimir Pavlovic, James M. Rehg, John MacCormick
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Learning Winner-Take-All Competition Between Groups of Neurons in Lateral Inhibitory Networks Xiaohui Xie, Richard H. R. Hahnloser, H. Sebastian Seung
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Machine Learning for Video-Based Rendering Arno Schödl, Irfan A. Essa
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Minimum Bayes Error Feature Selection for Continuous Speech Recognition George Saon, Mukund Padmanabhan
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Mixtures of Gaussian Processes Volker Tresp
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Model Complexity, Goodness of Fit and Diminishing Returns Igor V. Cadez, Padhraic Smyth
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Modelling Spatial Recall, Mental Imagery and Neglect Suzanna Becker, Neil Burgess
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Multiple Timescales of Adaptation in a Neural Code Adrienne L. Fairhall, Geoffrey D. Lewen, William Bialek, Robert R. de Ruyter van Steveninck
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Natural Sound Statistics and Divisive Normalization in the Auditory System Odelia Schwartz, Eero P. Simoncelli
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New Approaches Towards Robust and Adaptive Speech Recognition Hervé Bourlard, Samy Bengio, Katrin Weber
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Noise Suppression Based on Neurophysiologically-Motivated SNR Estimation for Robust Speech Recognition Jürgen Tchorz, Michael Kleinschmidt, Birger Kollmeier
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Occam's Razor Carl Edward Rasmussen, Zoubin Ghahramani
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On a Connection Between Kernel PCA and Metric Multidimensional Scaling Christopher K. I. Williams
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On Iterative Krylov-Dogleg Trust-Region Steps for Solving Neural Networks Nonlinear Least Squares Problems Eiji Mizutani, James Demmel
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On Reversing Jensen's Inequality Tony Jebara, Alex Pentland
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One Microphone Source Separation Sam T. Roweis
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Overfitting in Neural Nets: Backpropagation, Conjugate Gradient, and Early Stopping Rich Caruana, Steve Lawrence, C. Lee Giles
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Partially Observable SDE Models for Image Sequence Recognition Tasks Javier R. Movellan, Paul Mineiro, Ruth J. Williams
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Periodic Component Analysis: An Eigenvalue Method for Representing Periodic Structure in Speech Lawrence K. Saul, Jont B. Allen
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Permitted and Forbidden Sets in Symmetric Threshold-Linear Networks Richard H. R. Hahnloser, H. Sebastian Seung
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Place Cells and Spatial Navigation Based on 2D Visual Feature Extraction, Path Integration, and Reinforcement Learning Angelo Arleo, Fabrizio Smeraldi, Stéphane Hug, Wulfram Gerstner
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Position Variance, Recurrence and Perceptual Learning Zhaoping Li, Peter Dayan
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Probabilistic Semantic Video Indexing Milind R. Naphade, Igor Kozintsev, Thomas S. Huang
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Processing of Time Series by Neural Circuits with Biologically Realistic Synaptic Dynamics Thomas Natschläger, Wolfgang Maass, Eduardo D. Sontag, Anthony M. Zador
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Programmable Reinforcement Learning Agents David Andre, Stuart J. Russell
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Propagation Algorithms for Variational Bayesian Learning Zoubin Ghahramani, Matthew J. Beal
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Rate-Coded Restricted Boltzmann Machines for Face Recognition Yee Whye Teh, Geoffrey E. Hinton
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Recognizing Hand-Written Digits Using Hierarchical Products of Experts Guy Mayraz, Geoffrey E. Hinton
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Redundancy and Dimensionality Reduction in Sparse-Distributed Representations of Natural Objects in Terms of Their Local Features Penio S. Penev
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Regularization with Dot-Product Kernels Alex J. Smola, Zoltán L. Óvári, Robert C. Williamson
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Regularized Winnow Methods Tong Zhang
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Reinforcement Learning with Function Approximation Converges to a Region Geoffrey J. Gordon
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Robust Reinforcement Learning Jun Morimoto, Kenji Doya
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Second Order Approximations for Probability Models Hilbert J. Kappen, Wim Wiegerinck
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Sequentially Fitting ``Inclusive'' Trees for Inference in Noisy-or Networks Brendan J. Frey, Relu Patrascu, Tommi Jaakkola, Jodi Moran
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Sex with Support Vector Machines Baback Moghaddam, Ming-Hsuan Yang
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Shape Context: A New Descriptor for Shape Matching and Object Recognition Serge Belongie, Jitendra Malik, Jan Puzicha
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Smart Vision Chip Fabricated Using Three Dimensional Integration Technology Hiroyuki Kurino, M. Nakagawa, Kang Wook Lee, Tomonori Nakamura, Yuusuke Yamada, Ki Tae Park, Mitsumasa Koyanagi
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Some New Bounds on the Generalization Error of Combined Classifiers Vladimir Koltchinskii, Dmitriy Panchenko, Fernando Lozano
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Sparse Greedy Gaussian Process Regression Alex J. Smola, Peter L. Bartlett
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Sparse Kernel Principal Component Analysis Michael E. Tipping
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Sparse Representation for Gaussian Process Models Lehel Csató, Manfred Opper
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Sparsity of Data Representation of Optimal Kernel Machine and Leave-One-Out Estimator Adam Kowalczyk
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Speech Denoising and Dereverberation Using Probabilistic Models Hagai Attias, John C. Platt, Alex Acero, Li Deng
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Spike-Timing-Dependent Learning for Oscillatory Networks Silvia Scarpetta, Zhaoping Li, John A. Hertz
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Stability and Noise in Biochemical Switches William Bialek
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Stagewise Processing in Error-Correcting Codes and Image Restoration K. Y. Michael Wong, Hidetoshi Nishimori
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Structure Learning in Human Causal Induction Joshua B. Tenenbaum, Thomas L. Griffiths
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Support Vector Novelty Detection Applied to Jet Engine Vibration Spectra Paul M. Hayton, Bernhard Schölkopf, Lionel Tarassenko, Paul Anuzis
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Temporally Dependent Plasticity: An Information Theoretic Account Gal Chechik, Naftali Tishby
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Text Classification Using String Kernels Huma Lodhi, John Shawe-Taylor, Nello Cristianini, Christopher J. C. H. Watkins
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The Early Word Catches the Weights Mark A. Smith, Garrison W. Cottrell, Karen L. Anderson
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The Interplay of Symbolic and Subsymbolic Processes in Anagram Problem Solving David B. Grimes, Michael Mozer
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The Kernel Gibbs Sampler Thore Graepel, Ralf Herbrich
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The Kernel Trick for Distances Bernhard Schölkopf
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The Manhattan World Assumption: Regularities in Scene Statistics Which Enable Bayesian Inference James M. Coughlan, Alan L. Yuille
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The Missing Link - A Probabilistic Model of Document Content and Hypertext Connectivity David A. Cohn, Thomas Hofmann
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The Unscented Particle Filter Rudolph van der Merwe, Arnaud Doucet, Nando de Freitas, Eric A. Wan
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The Use of Classifiers in Sequential Inference Vasin Punyakanok, Dan Roth
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The Use of MDL to Select Among Computational Models of Cognition In Jae Myung, Mark A. Pitt, Shaobo Zhang, Vijay Balasubramanian
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Tree-Based Modeling and Estimation of Gaussian Processes on Graphs with Cycles Martin J. Wainwright, Erik B. Sudderth, Alan S. Willsky
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Universality and Individuality in a Neural Code Elad Schneidman, Naama Brenner, Naftali Tishby, Robert R. de Ruyter van Steveninck, William Bialek
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Using Free Energies to Represent Q-Values in a Multiagent Reinforcement Learning Task Brian Sallans, Geoffrey E. Hinton
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Using the Nyström Method to Speed up Kernel Machines Christopher K. I. Williams, Matthias Seeger
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Vicinal Risk Minimization Olivier Chapelle, Jason Weston, Léon Bottou, Vladimir Vapnik
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Weak Learners and Improved Rates of Convergence in Boosting Shie Mannor, Ron Meir
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What Can a Single Neuron Compute? Blaise Agüera y Arcas, Adrienne L. Fairhall, William Bialek
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Whence Sparseness? Carl van Vreeswijk
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Who Does What? a Novel Algorithm to Determine Function Localization Ranit Aharonov-Barki, Isaac Meilijson, Eytan Ruppin
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