index int64 0 20.3k | text stringlengths 0 1.3M | year stringdate 1987-01-01 00:00:00 2024-01-01 00:00:00 | No stringlengths 1 4 |
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2,100 | The Fidelity of Local Ordinal Encoding Javid Sadr, Sayan Mukherjee, Keith Thoresz, Pawan Sinha Center for Biological and Computational Learning Department of Brain and Cognitive Sciences, MIT Cambridge, Massachusetts, 02142 USA {sadr,sayan,thorek,sinha}@ai.mit.edu Abstract A key question in neuroscience i... | 2001 | 99 |
2,101 | Temporal Coherence, Natural Image Sequences, and the Visual Cortex Jarmo Hurri and Aapo Hyvärinen Neural Networks Research Centre Helsinki University of Technology P.O.Box 9800, 02015 HUT, Finland {jarmo.hurri,aapo.hyvarinen}@hut.fi Abstract We show that two important properties of the primary visual cor... | 2002 | 1 |
2,102 | How the Poverty of the Stimulus Solves the Poverty of the Stimulus WilleIll ZuideIlla Language Evolution and Computation Research Unit and Institute for Cell, Animal and Population Biology University of Edinburgh 40 George Square, Edinburgh EH8 9LL, United Kingdom jelle@ling.ed.ac.uk Abstract ... | 2002 | 10 |
2,103 | Morton-Style Factorial Coding of Color in Primary Visual Cortex Javier R. Movellan Institute for Neural Computation University of California San Diego La Jolla, CA 92093-0515 movellan@inc.ucsd.edu Thomas Wachtler Sloan Center for Theoretical Neurobiology The Salk Institute La Jolla, CA 92037, USA ... | 2002 | 100 |
2,104 | One-Class LP Classifier for Dissimilarity Representations El˙zbieta P˛ekalska1, David M.J.Tax2 and Robert P.W. Duin1 1Delft University of Technology, Lorentzweg 1, 2628 CJ Delft, The Netherlands 2Fraunhofer Institute FIRST.IDA, Kekuléstr.7, D-12489 Berlin, Germany ela@ph.tn.tudelft.nl,davidt@first.fraunhofer.d... | 2002 | 101 |
2,105 | Regularized Greedy Importance Sampling Finnegan Southey Dale Schuurmans Ali Ghodsi School of Computer Science University of Waterloo fdjsouth,dale,aghodsib @cs.uwaterloo.ca Abstract Greedy importance sampling is an unbiased estimation technique that reduces the variance of standard importance samp... | 2002 | 102 |
2,106 | Modeling Midazolam's Effect on the __H_il!Jlocampus and Recognition Memor! Kenneth J'" .I\'lalJrnbeJ~2 Departn1ent of Psychology Indiana V'uiversity Bloomington, IN' 47405 Rene Le!ele:nD~er2 Department of rS'/cnOlCHIV Indiana University Bloomington, IN 47405 rzeelenb(~~indiana.edu Richard 1\'1.. S... | 2002 | 103 |
2,107 | Fast Kernels for String and Tree Matching S. V. N. Vishwanathan Dept. of Compo Sci. & Automation Indian Institute of Science Bangalore, 560012, India vishy@csa . iisc . ernet . in Alexander J. Smola Machine Learning Group, RSISE Australian National University Canberra, ACT 0200, Australia ... | 2002 | 104 |
2,108 | Expected and Unexpected Uncertainty: ACh and NE in the Neocortex Angela Yu Peter Dayan Gatsby Computational Neuroscience Unit 17 Queen Square, London WC1N 3AR, United Kingdom. feraina@gatsby.ucl.ac.uk dayan@gatsby.ucl.ac.uk Abstract Inference and adaptation in noisy and changing, rich sensory environm... | 2002 | 105 |
2,109 | Feature Selection and Classification on Matrix Data: From Large Margins To Small Covering Numbers Sepp Hochreiter and Klaus Obermayer Department of Electrical Engineering and Computer Science Technische Universit¨at Berlin 10587 Berlin, Germany {hochreit,oby}@cs.tu-berlin.de Abstract We investigate the... | 2002 | 106 |
2,110 | Learning Semantic Similarity Jaz Kandola John Shawe-Taylor Royal Holloway, University of London {jaz, john}@cs.rhul.ac.uk N ella Cristianini University of California, Berkeley nello@support-vector.net Abstract The standard representation of text documents as bags of words suffers from well... | 2002 | 107 |
2,111 | How Linear are Auditory Cortical Responses? Maneesh Sahani Gatsby Unit, UCL 17 Queen Sq., London, WC1N 3AR, UK. maneesh@gatsby.ucl.ac.uk Jennifer F. Linden Keck Center, UCSF San Francisco, CA 94143–0732. linden@phy.ucsf.edu Abstract By comparison to some other sensory cortices, the functional proper... | 2002 | 108 |
2,112 | Incremental Gaussian Processes Joaquin Qui˜nonero-Candela Informatics and Mathematical Modelling Technical University of Denmark DK-2800 Lyngby, Denmark jqc@imm.dtu.dk Ole Winther Informatics and Mathematical Modelling Technical University of Denmark DK-2800 Lyngby, Denmark owi@imm.dtu.dk Abstract... | 2002 | 109 |
2,113 | Fast Transformation-Invariant Factor Analysis Anitha Kannan Nebojsa Jojic Brendan Frey University of Toronto, Toronto, Canada anitha, frey @psi.utoronto.ca Microsoft Research, Redmond, WA, USA jojic@microsoft.com Abstract Dimensionality reduction techniques such as principal component... | 2002 | 11 |
2,114 | Dynamic Bayesian Networks with Deterministic Latent Tables David Barber Institute for Adaptive and Neural Computation Edinburgh University 5 Forrest Hill, Edinburgh, EH1 2QL, U.K. dbarber@anc.ed.ac.uk Abstract The application of latent/hidden variable Dynamic Bayesian Networks is constrained by the comp... | 2002 | 110 |
2,115 | Generalized2 Linear2 Models Geoffrey J. Gordon ggordon@es.emu.edu Abstract We introduce the Generalized2 Linear2 Model, a statistical estimator which combines features of nonlinear regression and factor analysis. A (GL)2M approximately decomposes a rectangular matrix X into a simpler representation j(g(A... | 2002 | 111 |
2,116 | Spectro-Temporal Receptive Fields of Subthreshold Responses in Auditory Cortex Christian K. Machens, Michael Wehr, Anthony M. Zador Cold Spring Harbor Laboratory One Bungtown Rd Cold Spring Harbor, NY 11724 machens, wehr, zador @cshl.edu Abstract How do cortical neurons represent the acoustic envi... | 2002 | 112 |
2,117 | Bayesian Models of Inductive Generalization Neville E. Sanjana & Joshua B. Tenenbaum Department of Brain and Cognitive Sciences Massachusetts Institute of Technology Cambridge, MA 02139 nsanjana, jbt @mit.edu Abstract We argue that human inductive generalization is best explained in a Bayesian fra... | 2002 | 113 |
2,118 | Dynamical Constraints on Computing with Spike Timing in the Cortex Arunava Banerjee and Alexandre Pouget Department of Brain and Cognitive Sciences University of Rochester, Rochester, New York 14627 {arunavab, alex} @bcs.rochester.edu Abstract If the cortex uses spike timing to compute, the timing ... | 2002 | 114 |
2,119 | Bayesian Estimation of Time-Frequency Coefficients for Audio Signal Enhancement Patrick J. Wolfe Department of Engineering University of Cambridge Cambridge CB2 1PZ, UK pjw47@eng.cam.ac.uk Simon J. Godsill Department of Engineering University of Cambridge Cambridge CB2 1PZ, UK sjg@eng.cam.ac.uk ... | 2002 | 115 |
2,120 | Real-Time Monitoring of Complex Industrial Processes with Particle Filters Rub´en Morales-Men´endez Dept. of Mechatronics and Automation ITESM campus Monterrey Monterrey, NL M´exico rmm@itesm.mx Nando de Freitas and David Poole Dept. of Computer Science University of British Columbia Vancouver, BC,... | 2002 | 116 |
2,121 | Retinal Processing Emulation in a Programmable 2-Layer Analog Array Processor CMOS Chip R. Carmona, F. Jim´enez-Garrido, R. Dom´ınguez-Castro, S. Espejo, A. Rodr´ıguez-V´azquez Instituto de Microelectr´onica de Sevilla-CNM-CSIC Avda. Reina Mercedes s/n 41012 Sevilla (SPAIN) rcarmona@imse.cnm.es Abstract... | 2002 | 117 |
2,122 | Bayesian Image Super-Resolution Michael E. Tipping and Christopher M. Bishop Microsoft Research Cambridge, CB3 OFB, U.K. { mtipping, cmbishop} @microsoft.com http://research.microsoft.com/ "-'{ mtipping,cmbishop} Abstract The extraction of a single high-quality image from a set of lowresolution ima... | 2002 | 118 |
2,123 | Charting a Manifold Matthew Brand Mitsubishi Electric Research Labs 201 Broadway, Cambridge MA 02139 USA www.merl.com/people/brand/ Abstract We construct a nonlinear mapping from a high-dimensional sample space to a low-dimensional vector space, effectively recovering a Cartesian coordinate system for t... | 2002 | 119 |
2,124 | Spikernels: Embedding Spiking Neurons in Inner-Product Spaces Lavi Shpigelman Yoram Singer Rony Paz Eilon Vaadia School of computer Science and Engineering Interdisciplinary Center for Neural Computation Dept. of Physiology, Hadassah Medical School The Hebrew University J... | 2002 | 12 |
2,125 | A Minimal Intervention Principle for Coordinated Movement Emanuel Todorov Department of Cognitive Science University of California, San Diego todorov@cogsci.ucsd.edu Michael I. Jordan Computer Science and Statistics University of California, Berkeley jordan@cs.berkeley.edu Abstract Behavioral goal... | 2002 | 120 |
2,126 | A Probabilistic Approach to Single Channel Blind Signal Separation Gil-Jin Jang Spoken Language Laboratory KAIST, Daejon 305-701, South Korea jangbal@bawi.org http://speech.kaist.ac.kr/˜jangbal Te-Won Lee Institute for Neural Computation University of California, San Diego La Jolla, CA 92093, U.S.A.... | 2002 | 121 |
2,127 | A Digital Antennal Lobe for Pattern Equalization: Analysis and Design Alex Holub, Gilles Laurent and Pietro Perona Computation and Neural Systems, California Institute of Technology holub@caltech.edu, laurentg@caltech.edu, perona@caltech.edu Abstract Re-mapping patterns in order to equalize their dist... | 2002 | 122 |
2,128 | Knowledge-Based Support Vector Machine Classifiers Glenn M. Fung, Olvi L. Mangasarian and Jude W. Shavlik Computer Sciences Department, University of Wisconsin Madison, WI 53706 gfung, olvi, shavlik@cs.wisc.edu Abstract Prior knowledge in the form of multiple polyhedral sets, each belonging to one ... | 2002 | 123 |
2,129 | Conditional Models on the Ranking Poset Guy Lebanon School of Computer Science Carnegie Mellon University Pittsburgh, PA 15213 lebanon@cs.cmu.edu John Lafferty School of Computer Science Carnegie Mellon University Pittsburgh, PA 15213 lafferty@cs.cmu.edu Abstract A distance-based conditional mod... | 2002 | 124 |
2,130 | A Formulation for Minimax Probability Machine Regression Thomas Strohmann Department of Computer Science University of Colorado, Boulder strohman@cs.colorado.edu Gregory Z. Grudic Department of Computer Science University of Colorado, Boulder grudic@cs.colorado.edu Abstract We formulate the regres... | 2002 | 125 |
2,131 | Multiclass Learning by Probabilistic Embeddings Ofer Dekel and Yoram Singer School of Computer Science & Engineering The Hebrew University, Jerusalem 91904, Israel {oferd,singer}@cs.huji.ac.il Abstract We describe a new algorithmic framework for learning multiclass categorization problems. In this framework... | 2002 | 126 |
2,132 | Improving a Page Classifier with Anchor Extraction and Link Analysis William W. Cohen Center for Automated Learning and Discovery, Carnegie-Mellon University 5000 Forbes Ave, Pittsburgh, PA 15213 william@wcohen.com Abstract Most text categorization systems use simple models of documents and document co... | 2002 | 127 |
2,133 | VIBES: A Variational Inference Engine for Bayesian Networks Christopher M. Bishop Microsoft Research Cambridge, CB3 0FB, U.K. research.microsoft.com/∼cmbishop David Spiegelhalter MRC Biostatistics Unit Cambridge, U.K. david.spiegelhalter@mrc-bsu.cam.ac.uk John Winn Department of Physics Universi... | 2002 | 128 |
2,134 | A Convergent Form of Approximate Policy Iteration Theodore J. Perkins Department of Computer Science University of Massachusetts Amherst Amherst, MA 01003 perkins@cs.umass.edu Doina Precup School of Computer Science McGill University Montreal, Quebec, Canada H3A 2A7 dprecup@cs.mcgill.ca Abstract... | 2002 | 129 |
2,135 | Graph-Driven Features Extraction from Microarray Data using Diffusion Kernels and Kernel CCA Jean-Philippe Vert Ecole des Mines de Paris Jean-Philippe.Vert@mines.org Minoru Kanehisa Bioinformatics Center, Kyoto University kanehisa@kuicr.kyoto-u.ac.jp Abstract We present an algorithm to extract featu... | 2002 | 13 |
2,136 | Mean-Field Approach to a Probabilistic Model in Information Retrieval Bin Wu, K. Y. Michael Wong Department of Physics Hong Kong University of Science and Technology Clear Water Bay, Hong Kong phwbd@ust.hk phkywong@ust.hk David Bodoff Department of ISMT Hong Kong University of Science and Technology... | 2002 | 130 |
2,137 | Exponential Family PCA for Belief Compression in POMDPs Nicholas Roy Robotics Institute Carnegie Mellon University Pittsburgh, PA 15213 nickr@ri.cmu.edu Geoffrey Gordon Department of Computer Science Carnegie Mellon University Pittsburgh, PA 15213 ggordon@cs.cmu.edu Abstract Standard value fun... | 2002 | 131 |
2,138 | Dynamic Structure Super-Resolution Amos J Storkey Institute of Adaptive and Neural Computation Division of Informatics and Institute of Astronomy University of Edinburgh 5 Forrest Hill, Edinburgh UK a.storkey@ed.ac.uk Abstract The problem of super-resolution involves generating feasible higher resolut... | 2002 | 132 |
2,139 | Independent Components Analysis through Product Density Estimation 'frevor Hastie and Rob Tibshirani Department of Statistics Stanford University Stanford, CA, 94305 { hastie, tibs } @stat.stanford. edu Abstract We present a simple direct approach for solving the ICA problem, using density es... | 2002 | 133 |
2,140 | Discriminative Densities from Maximum Contrast Estimation Peter Meinicke Neuroinformatics Group University of Bielefeld Bielefeld, Germany pmeinick@techfak.uni-bielefeld.de Thorsten Twellmann Neuroinformatics Group University of Bielefeld Bielefeld, Germany ttwellma@techfak.uni-bielefeld.de Helg... | 2002 | 134 |
2,141 | Interpreting Neural Response Variability as Monte Carlo Sampling of the Posterior Patrik O. Hoyer and Aapo Hyv¨arinen Neural Networks Research Centre Helsinki University of Technology P.O. Box 9800, FIN-02015 HUT, Finland http://www.cis.hut.fi/phoyer/ patrik.hoyer@hut.fi Abstract The responses of co... | 2002 | 135 |
2,142 | Combining Features for BCI Guido Dornhege1∗, Benjamin Blankertz1, Gabriel Curio2, Klaus-Robert Müller1,3 1Fraunhofer FIRST.IDA, Kekuléstr. 7, 12489 Berlin, Germany 2Neurophysics Group, Dept. of Neurology, Klinikum Benjamin Franklin, Freie Universität Berlin, Hindenburgdamm 30, 12203 Berlin, Germany 3Universit... | 2002 | 136 |
2,143 | A Probabilistic Model for Learning Concatenative Morphology Matthew G. Snover Department of Computer Science Washington University St Louis, MO, USA, 63130-4809 ms9@cs.wustl.edu Michael R. Brent Department of Computer Science Washington University St Louis, MO, USA, 63130-4809 brent@cs.wustl.edu ... | 2002 | 137 |
2,144 | The Decision List Machine Marina Sokolova SITE, University of Ottawa Ottawa, Ont. Canada,K1N-6N5 sokolova@site.uottawa.ca Mario Marchand SITE, University of Ottawa Ottawa, Ont. Canada,K1N-6N5 marchand@site.uottawa.ca Nathalie Japkowicz SITE, University of Ottawa Ottawa, Ont. Canada,K1N-6N5 nat@s... | 2002 | 138 |
2,145 | How to Combine Color and Shape Information for 3D Object Recognition: Kernels do the Thick B. Caputo Smith-Kettlewell Eye Research Institute, 2318 Fillmore Street, 94115 San Francisco, California, USA caputo@ski.org Gy. Dorko Department of Computer Science, Chair for Pattern Recognition, ... | 2002 | 139 |
2,146 | Spike Timing-Dependent Plasticity in the Address Domain R. Jacob Vogelstein1, Francesco Tenore2, Ralf Philipp2, Miriam S. Adlerstein2, David H. Goldberg2 and Gert Cauwenberghs2 1Department of Biomedical Engineering 2Department of Electrical and Computer Engineering Johns Hopkins University, Baltimore, MD 21... | 2002 | 14 |
2,147 | Reconstructing Stimulus-Driven Neural Networks from Spike Times Duane Q. Nykamp UCLA Mathematics Department Los Angeles, CA 90095 nykamp@math.ucla.edu Abstract We present a method to distinguish direct connections between two neurons from common input originating from other, unmeasured neurons. The dist... | 2002 | 140 |
2,148 | Selectivity and Metaplasticity in a Unified Calcium-Dependent Model Luk Chong Yeung Physics Department and Institute for Brain & Neural Systems Brown University Providence, RI 02912 yeung@physics.brown.edu Brian S. Blais Department of Science & Technology Bryant College Smithfield, RI 02917 Instit... | 2002 | 141 |
2,149 | Learning to Detect Natural Image Boundaries Using Brightness and Texture David R. Martin Charless C. Fowlkes Jitendra Malik Computer Science Division, EECS, U.C. Berkeley, Berkeley, CA 94720 dmartin,fowlkes,malik @cs.berkeley.edu Abstract The goal of this work is to accurately detect and localize ... | 2002 | 142 |
2,150 | Concurrent Object Recognition and Segmentation by Graph Partitioning Stella x. YuH, Ralph Gross t and Jianbo Shit Robotics Institute t Carnegie Mellon University Center for the Neural Basis of Cognition+ 5000 Forbes Ave, Pittsburgh, PA 15213-3890 {stella.yu, rgross, jshi}@cs.cmu.edu Abstract ... | 2002 | 143 |
2,151 | Approximate Linear Programming for Average-Cost Dynamic Programming Daniela Pucci de Farias IBM Almaden Research Center 650 Harry Road, San Jose, CA 95120 pucci@mit.edu Benjamin Van Roy Department of Management Science and Engineering Stanford University Stanford, CA 94305 bvr@stanford.edu Abstrac... | 2002 | 144 |
2,152 | Learning Sparse Topographic Representations with Products of Student-t Distributions Max Welling and Geoffrey Hinton Department of Computer Science University of Toronto 10 King’s College Road Toronto, M5S 3G5 Canada welling,hinton @cs.toronto.edu Simon Osindero Gatsby Unit University College ... | 2002 | 145 |
2,153 | Margin Analysis of the LVQ Algorithm Koby Crammer kobics@cs.huji.ac.il Ran Gilad-Bachrach ranb@cs.huji.ac.il Amir Navot anavot@cs.huji.ac.il Naftali Tishby tishby@cs.huji.ac.il School of Computer Science and Engineering and Interdisciplinary Center for Neural Computation The Hebrew University, Jer... | 2002 | 146 |
2,154 | Feature Selection by Maximum Marginal Diversity Nuno Vasconcelos Department of Electrical and Computer Engineering University of California, San Diego nuno@media.mit.edu Abstract We address the question of feature selection in the context of visual recognition. It is shown that, besides efficient from a ... | 2002 | 147 |
2,155 | A Neural Edge-Detection Model for Enhanced Auditory Sensitivity in Modulated Noise Alon Fishbach and Bradford J. May Department of Biomedical Engineering and Otolaryngology-HNS Johns Hopkins University Baltimore, MD 21205 fishbach@northwestern.edu Abstract Psychophysical data sug... | 2002 | 148 |
2,156 | Concentration Inequalities for the Missing Mass and for Histogram Rule Error David McAllester Toyota Technological Institute at Chicago mcallester@tti-c.org Luis Ortiz University of Pennsylvania leo@cis.upenn.edu Abstract This paper gives distribution-free concentration inequalities for the missing ma... | 2002 | 149 |
2,157 | Efficient Learning Equilibrium * Ronen I. Brafman Computer Science Department Ben-Gurion University Beer-Sheva, Israel email: brafman@cs.bgu.ac.il Moshe Tennenholtz Computer Science Department Stanford University Stanford, CA 94305 e-mail: moshe@robotics.stanford.edu Abstract We intr... | 2002 | 15 |
2,158 | Learning Sparse Multiscale Image Representations Phil Sallee Department of Computer Science and Center for Neuroscience, UC Davis 1544 Newton Ct. Davis, CA 95616 sallee@cs.ucdavis.edu Bruno A. Olshausen Department of Psychology and Center for Neuroscience, UC Davis 1544 Newton Ct. Davis, CA 9561... | 2002 | 150 |
2,159 | The Effect of Singularities in a Learning Machine when the True Parameters Do Not Lie on Such Singularities Sumio Watanabe Precision and Intelligence Laboratory Tokyo Institute of Technology 4259 Nagatsuta, Midori-ku, Yokohama, 226-8503 Japan E-mail: swatanab@pi.titech.ac.jp Shun-ichi Amari Laboratory ... | 2002 | 151 |
2,160 | Learning about Multiple Objects in Images: Factorial Learning without Factorial Search Christopher K. I. Williams and Michalis K. Titsias School of Informatics, University of Edinburgh, Edinburgh EH1 2QL, UK c.k.i.williams@ed.ac.uk M.Titsias@sms.ed.ac.uk Abstract We consider data which are images conta... | 2002 | 152 |
2,161 | Distance Metric Learning, with Application to Clustering with Side-Information Eric P. Xing, Andrew Y. Ng, Michael I. Jordan and Stuart Russell University of California, Berkeley Berkeley, CA 94720 epxing,ang,jordan,russell @cs.berkeley.edu Abstract Many algorithms rely critically on being given a g... | 2002 | 153 |
2,162 | Location Estimation with a Differential Update Network Ali Rahimi and Trevor Darrell Artificial Intelligence Laboratory Massachusetts Institute of Technology Cambridge, MA 02139 {ali,trevor}@mit.edu Abstract Given a set of hidden variables with an a-priori Markov structure, we derive an online algorith... | 2002 | 154 |
2,163 | Hyperkernels Cheng Soon Ong, Alexander J. Smola, Robert C. Williamson Research School of Information Sciences and Engineering The Australian National University Canberra, 0200 ACT, Australia Cheng.Ong, Alex.Smola, Bob.Williamson @anu.edu.au Abstract We consider the problem of choosing a kernel suita... | 2002 | 155 |
2,164 | Prediction and Semantic Association Thomas L. Griffiths & Mark Steyvers Department of Psychology Stanford University, Stanford, CA 94305-2130 {gruffydd,msteyver}@psych.stanford.edu Abstract We explore the consequences of viewing semantic association as the result of attempting to predict the concep... | 2002 | 156 |
2,165 | A Maximum Entropy Approach To Collaborative Filtering in Dynamic, Sparse, High-Dimensional Domains Dmitry Y. Pavlov NEC Laboratories America 4 Independence Way Princeton, NJ 08540, dpavlov@nec-labs.com David M. Pennock Overture Services, Inc. 74 N. Pasadena Ave., 3rd floor Pasadena, CA 91103, dav... | 2002 | 157 |
2,166 | Annealing and the Rate Distortion Problem Albert E. Parker Department of Mathematical Sciences Montana State University Bozeman, MT 59771 parker@math.montana.edu Tom´aˇs Gedeon Department of Mathematical Sciences Montana State University gedeon@math.montana.edu Alexander G. Dimitrov Center for Com... | 2002 | 158 |
2,167 | Self Supervised Boosting Max Welling, Richard S. Zemel, and Geoffrey E. Hinton Department of Computer Science University of Toronto 10 King’s College Road Toronto, M5S 3G5 Canada Abstract Boosting algorithms and successful applications thereof abound for classification and regression learning problems, but... | 2002 | 159 |
2,168 | Using Tarjan’s Red Rule for Fast Dependency Tree Construction Dan Pelleg and Andrew Moore School of Computer Science Carnegie-Mellon University Pittsburgh, PA 15213 USA dpelleg@cs.cmu.edu, awm@cs.cmu.edu Abstract We focus on the problem of efficient learning of dependency trees. It is well-known that g... | 2002 | 16 |
2,169 | An Estimation-Theoretic Framework for the Presentation of Multiple Stimuli Christian W. Eurich∗ Institute for Theoretical Neurophysics University of Bremen Otto-Hahn-Allee 1 D-28359 Bremen, Germany eurich@physik.uni-bremen.de Abstract A framework is introduced for assessing the encoding accuracy and ... | 2002 | 160 |
2,170 | Convergent Combinations of Reinforcement Learning with Linear Function Approximation Ralf Schoknecht ILKD University of Karlsruhe, Germany ralf. schoknecht@ilkd. uni-karlsruhe. de Artur Merke Lehrstuhl Informatik 1 University of Dortmund, Germany arturo merke@udo.edu Abstract Converg... | 2002 | 161 |
2,171 | Informed Projections David Cohn Carnegie Mellon University Pittsburgh, PA 15213 cohn+@cs.cmu.edu Abstract Low rank approximation techniques are widespread in pattern recognition research — they include Latent Semantic Analysis (LSA), Probabilistic LSA, Principal Components Analysus (PCA), the Generative Asp... | 2002 | 162 |
2,172 | Automatic Acquisition and Efficient Representation of Syntactic Structures Zach Solan, Eytan Ruppin, David Horn Faculty of Exact Sciences Tel Aviv University Tel Aviv, Israel 69978 {rsolan,ruppin,horn}@post.tau.ac.il Shimon Edelman Department of Psychology Cornell University Ithaca, NY 14853, USA s... | 2002 | 163 |
2,173 | Application of Variational Bayesian Approach to Speech Recognition Shinji Watanabe, Yasuhiro Minami, Atsushi Nakamura and Naonori Ueda NTT Communication Science Laboratories, NTT Corporation 2-4, Hikaridai, Seika-cho, Soraku-gun, Kyoto, Japan {watanabe,minami,ats,ueda}@cslab.kecl.ntt.co.jp Abstract In thi... | 2002 | 164 |
2,174 | Stable Fixed Points of Loopy Belief Propagation Are Minima of the Bethe Free Energy Tom Heskes SNN, University of Nijmegen Geert Grooteplein 21, 6252 EZ, Nijmegen, The Netherlands Abstract We extend recent work on the connection between loopy belief propagation and the Bethe free energy. Constrained min... | 2002 | 165 |
2,175 | Identity Uncertainty and Citation Matching Hanna Pasula, Bhaskara Marthi, Brian Milch, Stuart Russell, Ilya Shpitser Computer Science Division, University Of California 387 Soda Hall, Berkeley, CA 94720-1776 pasula, marthi, milch, russell, ilyas@cs.berkeley.edu Abstract Identity uncertainty is a pervasive p... | 2002 | 166 |
2,176 | Fast Sparse Gaussian Process Methods: The Informative Vector Machine Neil Lawrence University of Sheffield 211 Portobello Street Sheffield, S1 4DP neil@dcs.shef.ac.uk Matthias Seeger University of Edinburgh 5 Forrest Hill Edinburgh, EH1 2QL seeger@dai.ed.ac.uk Ralf Herbrich Microsoft Research Ltd ... | 2002 | 167 |
2,177 | Recovering Articulated Model Topology from Observed Rigid Motion Leonid Taycher, John W. Fisher III, and Trevor Darrell Artificial Intelligence Laboratory Massachusetts Institute of Technology Cambridge, MA, 02139 {lodrion, fisher, trevor}@ai.mit.edu Abstract Accurate representation of articulated motion ... | 2002 | 168 |
2,178 | Learning to Perceive Transparency from the Statistics of Natural Scenes Anat Levin Assaf Zomet Yair Weiss School of Computer Science and Engineering The Hebrew University of Jerusalem 91904 Jerusalem, Israel {alevin,zomet,yweiss}@cs.huji.ac.il Abstract Certain simple images are known to trigger a pe... | 2002 | 169 |
2,179 | Approximate Inference and Protein-Folding Chen Yanover and Yair Weiss School of Computer Science and Engineering The Hebrew University of Jerusalem 91904 Jerusalem, Israel {cheny,yweiss} @cs.huji.ac.it Abstract Side-chain prediction is an important subtask in the protein-folding problem. We s... | 2002 | 17 |
2,180 | Replay, Repair and Consolidation Szabolcs K´ali Peter Dayan Institute of Experimental Medicine Gatsby Computational Neuroscience Unit Hungarian Academy of Sciences University College London Budapest 1450, Hungary 17 Queen Square, London WC1N 3AR, U.K. kali@koki.hu dayan@gatsby.ucl.ac.uk Abstract ... | 2002 | 170 |
2,181 | Inferring a Semantic Representation of Text via Cross-Language Correlation Analysis Alexei Vinokourov John Shawe-Taylor Dept. Computer Science Royal Holloway, University of London Egham, Surrey, UK, TW20 0EX alexei@cs.rhul.ac.uk john@cs.rhul.ac.uk Nello Cristianini Dept. Statistics UC Davis, Berke... | 2002 | 171 |
2,182 | Cluster Kernels for Semi-Supervised Learning Olivier Chapelle, Jason Weston, Bernhard Scholkopf Max Planck Institute for Biological Cybernetics, 72076 Tiibingen, Germany {first. last} @tuebingen.mpg.de Abstract We propose a framework to incorporate unlabeled data in kernel classifier, based on the ... | 2002 | 172 |
2,183 | A Hierarchical Bayesian Markovian Model for Motifs in Biopolymer Sequences Eric P. Xing, Michael I. Jordan, Richard M. Karp and Stuart Russell Computer Science Division University of California, Berkeley Berkeley, CA 94720 epxing,jordan,karp,russell @cs.berkeley.edu Abstract We propose a dynamic B... | 2002 | 173 |
2,184 | Speeding up the Parti-Game Algorithm Maxim Likhachev School of Computer Science Carnegie Mellon University Pittsburgh, PA 15213 maxim+@cs.cmu.edu Sven Koenig College of Computing Georgia Institute of Technology Atlanta, GA 30312-0280 skoenig@cc.gatech.edu Abstract In this paper, we introduce an ... | 2002 | 174 |
2,185 | Kernel-based Extraction of Slow Features: Complex Cells Learn Disparity and Translation Invariance from Natural Images Alistair Bray and Dominique Martinez* CORTEX Group, LORIA-INRIA, Nancy, France bray@loria.fr, dmartine@loria.jr Abstract In Slow Feature Analysis (SFA [1]), it has been demonstrated t... | 2002 | 175 |
2,186 | Monaural Speech Separation Guoning Hu DeLiang Wang Biophysics Program Department of Computer and Information The Ohio State University Science & Center of Cognitive Science Columbus, OH 43210 The Ohio State University, Columbus, OH 43210 hu.117@osu.edu dwang@ci... | 2002 | 176 |
2,187 | Multiplicative Updates for Nonnegative Quadratic Programming in Support Vector Machines Fei Sha1, Lawrence K. Saul1, and Daniel D. Lee2 1Department of Computer and Information Science 2Department of Electrical and System Engineering University of Pennsylvania 200 South 33rd Street, Philadelphia, PA 19104 ... | 2002 | 177 |
2,188 | Kernel Design Using Boosting Koby Crammer Joseph Keshet Yoram Singer School of Computer Science & Engineering The Hebrew University, Jerusalem 91904, Israel {kobics,jkeshet,singer}@cs.huji.ac.il Abstract The focus of the paper is the problem of learning kernel operators from empirical data. We cast th... | 2002 | 178 |
2,189 | Rational Kernels Corinna Cortes Patrick Haffner Mehryar Mohri AT&T Labs – Research 180 Park Avenue, Florham Park, NJ 07932, USA corinna, haffner, mohri @research.att.com Abstract We introduce a general family of kernels based on weighted transducers or rational relations, rational kernels, that ca... | 2002 | 179 |
2,190 | Learning a Forward Model of a Reflex Bernd Porr and Florentin W¨org¨otter Computational Neuroscience Psychology University of Stirling FK9 4LR Stirling, UK bp1,faw1 @cn.stir.ac.uk Abstract We develop a systems theoretical treatment of a behavioural system that interacts with its environment in a ... | 2002 | 18 |
2,191 | Linear Combinations of Optic Flow Vectors for Estimating Self-Motion –a Real-World Test of a Neural Model Matthias O. Franz MPI f¨ur biologische Kybernetik Spemannstr. 38 D-72076 T¨ubingen, Germany mof@tuebingen.mpg.de Javaan S. Chahl Center of Visual Sciences, RSBS Australian National University ... | 2002 | 180 |
2,192 | Kernel Dependency Estimation Jason Weston, Olivier Chapelle, Andre Elisseeff, Bernhard Scholkopf and Vladimir Vapnik* Max Planck Institute for Biological Cybernetics, 72076 Tubingen, Germany *NEC Research Institute, Princeton, NJ 08540 USA Abstract We consider the learning problem of finding a depende... | 2002 | 181 |
2,193 | Circuit Model of Short-Term Synaptic Dynamics Shih-Chii Liu, Malte Boegershausen, and Pascal Suter Institute of Neuroinformatics University of Zurich and ETH Zurich Winterthurerstrasse 190 CH-8057 Zurich, Switzerland shih@ini.phys.ethz.ch Abstract We describe a model of short-term synaptic depression th... | 2002 | 182 |
2,194 | Coulomb Classifiers: Generalizing Support Vector Machines via an Analogy to Electrostatic Systems Sepp Hochreiter†, Michael C. Mozer∗, and Klaus Obermayer† †Department of Electrical Engineering and Computer Science Technische Universit¨at Berlin, 10587 Berlin, Germany ∗Department of Computer Science Univer... | 2002 | 183 |
2,195 | Robust Novelty Detection with Single-Class MPM Gert R.G. Lanckriet EECS, V.C. Berkeley gert@eecs.berkeley. edu Laurent EI Ghaoui EECS, V.C. Berkeley elghaoui@eecs.berkeley.edu Abstract Michael I. Jordan Computer Science and Statistics, V.C. Berkeley jordan@cs. berkeley. edu In thi... | 2002 | 184 |
2,196 | Binary Thning is Optimal for eural Rate Coding with High Temporal Resolution Matthias Bethge:David Rotermund, and Klaus Pawelzik Institute of Theoretical Physics University of Bremen 28334 Bremen {mbethge,davrot,pawelzik}@physik.uni-bremen.de Abstract Here we derive optimal gain functions for minimum ... | 2002 | 185 |
2,197 | Feature Selection in Mixture-Based Clustering Martin H. Law, Anil K. Jain Dept. of Computer Science and Eng. Michigan State University, East Lansing, MI 48824 U.S.A. M´ario A. T. Figueiredo Instituto de Telecomunicac¸˜oes, Instituto Superior T´ecnico 1049-001 Lisboa Portugal Abstract There exist... | 2002 | 186 |
2,198 | Minimax Differential Dynamic Programming: An Application to Robust Biped Walking Jun Morimoto Human Information Science Labs, Department 3, ATR International Keihanna Science City, Kyoto, JAPAN, 619-0288 xmorimo@atr.co.jp Christopher G. Atkeson ∗ The Robotics Institute and HCII, Carnegie Mellon Univ... | 2002 | 187 |
2,199 | Theory-Based Causal Inference Joshua B. Tenenbaum & Thomas L. Griffiths Department of Brain and Cognitive Sciences MIT, Cambridge, MA 02139 jbt, gruffydd @mit.edu Abstract People routinely make sophisticated causal inferences unconsciously, effortlessly, and from very little data – often from just one ... | 2002 | 188 |
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