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2,000 | MIME: Mutual Information Minimization and Entropy Maximization for Bayesian Belief Propagation Anand Rangarajan Dept. of Computer and Information Science and Engineering University of Florida Gainesville, FL 32611-6120, US anand@cise.ufl.edu Alan L. Yuille Smith-Kettlewell Eye Research Institute 2318... | 2001 | 186 |
2,001 | Rates of Convergence of Performance Gradient Estimates Using Function Approximation and Bias in Reinforcement Learning Gregory Z. Grudic University of Colorado, Boulder grudic@cs.colorado.edu Lyle H. Ungar University of Pennsylvania ungar@cis.upenn.edu Abstract We address two open theoretical questi... | 2001 | 187 |
2,002 | A Generalization of Principal Component Analysis to the Exponential Family Michael Collins Sanjoy Dasgupta Robert E. Schapire AT&T Labs Research 180 Park Avenue, Florham Park, NJ 07932 mcollins, dasgupta, schapire @research.att.com Abstract Principal component analysis (PCA) is a commonly app... | 2001 | 188 |
2,003 | Minimax Probability Machine Gert R.G. Lanckriet* Department of EECS University of California, Berkeley Berkeley, CA 94720-1770 gert@eecs.berkeley.edu Chiranjib Bhattacharyya Department of EECS University of California, Berkeley Berkeley, CA 94720-1776 chiru@eecs.berkeley.edu Laurent EI ... | 2001 | 189 |
2,004 | Agglomerative Multivariate Information Bottleneck Noam Sionim Nir Friedman Naftali Tishby School of Computer Science & Engineering, Hebrew University, Jerusalem 91904, Israel {noamm, nir, tishby } @cs.huji.ac.il Abstract The information bottleneck method is an unsupervised model independent data... | 2001 | 19 |
2,005 | Duality, Geometry, and Support Vector Regression Jinbo Bi and Kristin P. Bennett Department of Mathematical Sciences Rensselaer Polytechnic Institute Troy, NY 12180 bij2@rpi.edu, bennek@rpi.edu Abstract We develop an intuitive geometric framework for support vector regression (SVR). By examining w... | 2001 | 190 |
2,006 | BLIND SOURCE SEPARATION VIA MULTINODE SPARSE REPRESENTATION Michael Zibulevsky Department of Electrical Engineering Technion, Haifa 32000, Israel mzib@ee.technion.ac. if Yehoshua Y. Zeevi Department of Electrical Engineering Technion, Haifa 32000, Israel zeevi@ee.technion.ac. if Pavel Kisi... | 2001 | 191 |
2,007 | Estimating the Reliability of leA Projections F. Meinecke l ,2, A. Ziehel , M. Kawanabel and K.-R. Miillerl ,2* 1 Fraunhofer FIRST.IDA, Kekuh~str. 7, 12489 Berlin, Germany 2University of Potsdam, Am Neuen Palais 10, 14469 Potsdam, Germany {meinecke,ziehe,nabe,klaus}©first.fhg.de Abstract When apply... | 2001 | 192 |
2,008 | Learning from Infinite Data in Finite Time Pedro Domingos Geoff H ulten Department of Computer Science and Engineering University of Washington Seattle, WA 98185-2350, U.S.A. {pedrod, ghulten} @cs.washington.edu Abstract We propose the following general method for scaling learning algorith... | 2001 | 193 |
2,009 | The 9 Factor: Relating Distributions on Features to Distributions on Images James M. Coughlan and A. L. Yuille Smith-Kettlewell Eye Research Institute, 2318 Fillmore Street, San Francisco, CA 94115, USA. Tel. (415) 345-2146/2144. Fax. (415) 345-8455. Email: coughlan@ski.org.yuille@ski.org Abstra... | 2001 | 194 |
2,010 | Distribution of Mutual Information Marcus Hutter IDSIA, Galleria 2, CH-6928 Manno-Lugano, Switzerland marcus@idsia.ch http://www.idsia.ch/- marcus Abstract The mutual information of two random variables z and J with joint probabilities {7rij} is commonly used in learning Bayesian nets as well as... | 2001 | 195 |
2,011 | A Maximum-Likelihood Approach to Modeling Multisensory Enhancement Hans Colonius* Institut fUr Kognitionsforschung Carl von Ossietzky Universitat Oldenburg, D-26111 hans. colonius@uni-oldenburg.de Adele Diederich School of Social Sciences International University Bremen Bremen, D-28725 ... | 2001 | 196 |
2,012 | Model-Free Least Squares Policy Iteration Michail G. Lagoudakis Department of Computer Science Duke University Durham, NC 27708 mgl@cs.duke.edu Ronald Parr Department of Computer Science Duke University Durham, NC 27708 parr@cs.duke.edu Abstract We propose a new approach to reinforcement learnin... | 2001 | 197 |
2,013 | Fragment completion in humans and machines David Jacobs NEC Research Institute 4 Independence Way, Princeton, NJ 08540 dwj@research.nj.nec.com Bas Rokers Psychology Department at UCLA PO Box 951563, Los Angeles, CA 90095 rokers@psych.ucla.edu Archisman Rudra CS Department at NYU 251 Mercer St., Ne... | 2001 | 2 |
2,014 | K-Local Hyperplane and Convex Distance Nearest Neighbor Algorithms Pascal Vincent and Yoshua Bengio Dept. IRO, Universit´e de Montr´eal C.P. 6128, Montreal, Qc, H3C 3J7, Canada vincentp,bengioy @iro.umontreal.ca http://www.iro.umontreal.ca/ vincentp Abstract Guided by an initial idea of buildi... | 2001 | 20 |
2,015 | Thomas L .. Griffiths & Joshua B. Tenenbaum Department of Psychology Stanford University, Stanford, CA 94305 {gruffydd,jbt}©psych. stanford. edu Abstract Estimating the parameters of sparse multinomial distributions is an important component of many statistical learning tasks. Recent approaches have used ... | 2001 | 21 |
2,016 | Bayesian time series classification Peter Sykacek Department of Engineering Science University of Oxford Oxford, OX1 3PJ, UK psyk@robots.ox.ac.uk Stephen Roberts Department of Engineering Science University of Oxford Oxford, OX1 3PJ, UK sjrob@robots.ox.ac.uk Abstract This paper proposes an approa... | 2001 | 22 |
2,017 | Computing Time Lower Bounds for Recurrent Sigmoidal Neural Networks Michael Schmitt Lehrstuhl Mathematik und Informatik, Fakultat fUr Mathematik Ruhr-Universitat Bochum, D- 44780 Bochum, Germany mschmitt@lmi.ruhr-uni-bochum.de Abstract Recurrent neural networks of analog units are computers for rea... | 2001 | 23 |
2,018 | Playing is believing: The role of beliefs in multi-agent learning Yu-Han Chang Artificial Intelligence Laboratory Massachusetts Institute of Technology Cambridge, Massachusetts 02139 ychang@ai.mit.edu Leslie Pack Kaelbling Artificial Intelligence Laboratory Massachusetts Institute of Technology Cambri... | 2001 | 24 |
2,019 | Probabilistic principles in unsupervised learning of visual structure: human data and a model Shimon Edelman, Benjamin P. Hiles & Hwajin Yang Department of Psychology Cornell University, Ithaca, NY 14853 se37,bph7,hy56 @cornell.edu Nathan Intrator Institute for Brain and Neural Systems Box 1843,... | 2001 | 25 |
2,020 | Predictive Representations of State Michael L. Littman Richard S. Sutton AT&T Labs-Research, Florham Park, New Jersey {mlittman,sutton}~research.att.com Satinder Singh Syntek Capital, New York, New York baveja~cs.colorado.edu Abstract We show that states of a dynamical system can be usefully represent... | 2001 | 26 |
2,021 | Discriminative Direction for Kernel Classifiers Polina Golland Artificial Intelligence Lab Massachusetts Institute of Technology Cambridge, MA 02139 polina@ai.mit.edu Abstract In many scientific and engineering applications, detecting and understanding differences between two groups of examples can be reduce... | 2001 | 27 |
2,022 | Contextual Modulation of Target Saliency Antonio Torralba Dept. of Brain and Cognitive Sciences MIT, Cambridge, MA 02139 torralba@ai.mit. edu Abstract The most popular algorithms for object detection require the use of exhaustive spatial and scale search procedures. In such approaches, an object is defi... | 2001 | 28 |
2,023 | On Kernel-Target Alignment N ello Cristianini BIOwulf Technologies nello@support-vector. net Andre Elisseeff BIOwulf Technologies andre@barnhilltechnologies.com John Shawe-Taylor Royal Holloway, University of London john@cs.rhul.ac.uk Jaz Kandola Royal Holloway, University of London ... | 2001 | 29 |
2,024 | Eye movements and the maturation of cortical orientation selectivity Michele Rucci and Antonino Casile Department of Cognitive and Neural Systems, Boston University, Boston, MA 02215. Scuola Superiore S. Anna, Pisa, Italy Abstract Neural activity appears to be a crucial component for shaping the... | 2001 | 3 |
2,025 | Escaping the Convex Hull with Extrapolated Vector Machines. Patrick Haffner AT&T Labs-Research, 200 Laurel Ave, Middletown, NJ 07748 haffner@research.att.com Abstract Maximum margin classifiers such as Support Vector Machines (SVMs) critically depends upon the convex hulls of the training sample... | 2001 | 30 |
2,026 | Algorithmic Luckiness Ralf Herbrich Microsoft Research Ltd. CB3 OFB Cambridge United Kingdom rherb@microsoft·com Robert C. Williamson Australian National University Canberra 0200 Australia Bob. Williamson@anu.edu.au Abstract In contrast to standard statistical learning theory which s... | 2001 | 31 |
2,027 | Optimising Synchronisation Times for Mobile Devices Neil D. Lawrence Department of Computer Science, Regent Court, 211 Portobello Road, Sheffield, Sl 4DP, U.K. neil~dcs.shef . ac.uk Antony 1. T. Rowstron Christopher M . Bishop Michael J. Taylor Microsoft Research 7 J. J. Thomson A venue ... | 2001 | 32 |
2,028 | Spike timing and the coding of naturalistic sounds in a central auditory area of songbirds Brian D. Wright, Kamal Sen, William Bialek and Allison J. Doupe Sloan–Swartz Center for Theoretical Neurobiology Departments of Physiology and Psychiatry Universit... | 2001 | 33 |
2,029 | A Variational Approach to Learning Curves D¨orthe Malzahn Manfred Opper Neural Computing Research Group School of Engineering and Applied Science Aston University, Birmingham B4 7ET, United Kingdom. [malzahnd,opperm]@aston.ac.uk Abstract We combine the replica approach from statistical physics with a va... | 2001 | 34 |
2,030 | Why neuronal dynamics should control synaptic learning rules Jesper Tegner Stockholm Bioinformatics Center Dept. of Numerical Analysis & Computing Science Royal Institute for Technology S-10044 Stockholm, Sweden jespert@nada.kth.se Adam Kepecs Volen Center for Complex Systems Brandeis U... | 2001 | 35 |
2,031 | Latent Dirichlet Allocation David M. Blei, Andrew Y. Ng and Michael I. Jordan University of California, Berkeley Berkeley, CA 94720 Abstract We propose a generative model for text and other collections of discrete data that generalizes or improves on several previous models including naive Bayes/unigr... | 2001 | 36 |
2,032 | A Bayesian Network for Real-Time Musical Accompaniment Christopher Raphael Department of Mathematics and Statistics, University of Massachusetts at Amherst, Amherst, MA 01003-4515, raphael~math.umass.edu Abstract We describe a computer system that provides a real-time musical accompaniment for a... | 2001 | 37 |
2,033 | Efficiency versus Convergence of Boolean Kernels for On-Line Learning Algorithms Roni Khardon Tufts University Medford, MA 02155 roni@eecs.tufts.edu Dan Roth University of Illinois Urbana, IL 61801 danr@cs.uiuc.edu Rocco Servedio Harvard University Cambridge, MA 02138 rocco@deas.harvard.edu A... | 2001 | 38 |
2,034 | Prodding the ROC Curve: Constrained Optimization of Classifier Performance Michael C. Mozer*+, Robert Dodier*, Michael D. Colagrosso*+, César Guerra-Salcedo*, Richard Wolniewicz* * Advanced Technology Group + Department of Computer Science Athene Software University of Colorado 2060 Broadway Campus Box... | 2001 | 39 |
2,035 | Orientation-Selective aVLSI Spiking Neurons Shih-Chii Liu, J¨org Kramer, Giacomo Indiveri, Tobias Delbr¨uck, and Rodney Douglas Institute of Neuroinformatics University of Zurich and ETH Zurich Winterthurerstrasse 190 CH-8057 Zurich, Switzerland Abstract We describe a programmable multi-chip VLSI neuron... | 2001 | 4 |
2,036 | Natural Language Grammar Induction using a Constituent-Context Model Dan Klein and Christopher D. Manning Computer Science Department Stanford University Stanford, CA 94305-9040 {klein, manning}@cs.stanford.edu Abstract This paper presents a novel approach to the unsupervised learning of syntactic analy... | 2001 | 40 |
2,037 | Estimating Car Insurance Premia: a Case Study in High-Dimensional Data Inference Nicolas Chapados, Yoshua Bengio, Pascal Vincent, Joumana Ghosn, Charles Dugas, Ichiro Takeuchi, Linyan Meng University of Montreal, dept. IRQ, CP 6128, Succ. Centre-Ville, Montreal, Qc, Canada, H3C3J7 {chapadosJbengioy,vincentp... | 2001 | 41 |
2,038 | Classifying Single Trial EEG: Towards Brain Computer Interfacing Benjamin Blankertz1∗, Gabriel Curio2 and 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 Be... | 2001 | 42 |
2,039 | Kernel Logistic Regression and the Import Vector Machine Ji Zhu Department of Statistics Stanford University Stanford, CA 94305 jzhu@stat.stanford.edu Trevor Hastie Department of Statistics Stanford University Stanford, CA 94305 hastie@stat.stanford.edu Abstract The support vector machine (SVM... | 2001 | 43 |
2,040 | A Model of the Phonological Loop: Generalization and Binding Randall C. O'Reilly Department of Psychology University of Colorado Boulder 345 UCB Boulder, CO 80309 oreilly@psych.colorado.edu Rodolfo Soto Department of Psychology University of Colorado Boulder 345 UCB Boulder, CO 80309... | 2001 | 44 |
2,041 | Thin Junction Trees Francis R. Bach Computer Science Division University of California Berkeley, CA 94720 fbach@cs.berkeley.edu Michael I. Jordan Computer Science and Statistics University of California Berkeley, CA 94720 jordan@cs.berkeley.edu Abstract We present an algorithm that induces a cla... | 2001 | 45 |
2,042 | Linking motor learning to function approximation: Learning in an unlearnable force field Opher Donchin and Reza Shadmehr Dept. of Biomedical Engineering Johns Hopkins University, Baltimore, MD 21205 Email: opher@bme.jhu.edu, reza@bme.jhu.edu Abstract Reaching movements require the brain to generate motor... | 2001 | 46 |
2,043 | A Parallel Mixture of SVMs for Very Large Scale Problems Ronan Collobert* Universite de Montreal, DIRG CP 6128, Succ. Centre-Ville Montreal, Quebec, Canada collober©iro.umontreal.ca Samy Bengio IDIAP CP 592, rue du Simp Ion 4 1920 Martigny, Switzerland bengio©idiap.ch Yoshua Bengio ... | 2001 | 47 |
2,044 | Switch Packet Arbitration via Queue-Learning Timothy X Brown Electrical and Computer Engineering Interdisciplinary Telecommunications University of Colorado Boulder, CO 80309-0530 timxb@colorado.edu Abstract In packet switches, packets queue at switch inputs and contend for outputs. The contention arbit... | 2001 | 48 |
2,045 | Multi Dimensional ICA to Separate Correlated Sources Roland Vollgraf, Klaus Obermayer Department of Electrical Engineering and Computer Science Technical University of Berlin Germany { vro, oby} @cs.tu-berlin.de Abstract We present a new method for the blind separation of sources, which do not f... | 2001 | 49 |
2,046 | On the Generalization Ability of On-line Learning Algorithms Nicol`o Cesa-Bianchi DTI, University of Milan via Bramante 65 26013 Crema, Italy cesa-bianchi@dti.unimi.it Alex Conconi DTI, University of Milan via Bramante 65 26013 Crema, Italy conconi@dti.unimi.it Claudio Gentile DSI, University ... | 2001 | 5 |
2,047 | Effective size of receptive fields of inferior temporal visual cortex neurons in natural scenes Thomas P. Trappenberg Dalhousie University Faculty of Computer Science 5060 University Avenue, Halifax B3H 1W5, Canada tt@cs.dal.ca Edmund T. Rolls and Simon M. Stringer University of Oxford, Centre for Comp... | 2001 | 50 |
2,048 | A kernel method for multi-labelled classification Andr´e Elisseeff and Jason Weston BIOwulf Technologies, 305 Broadway, New York, NY 10007 andre,jason @barhilltechnologies.com Abstract This article presents a Support Vector Machine (SVM) like learning system to handle multi-label problems. Such problems ... | 2001 | 51 |
2,049 | Learning Lateral Interactions for Feature Binding and Sensory Segmentation Heiko Wersing HONDA R&D Europe GmbH Carl-Legien-Str.30, 63073 Offenbach/Main, Germany heiko.wersing@hre-ftr.f.rd.honda.co.jp Abstract We present a new approach to the supervised learning of lateral interactions for the competitive ... | 2001 | 52 |
2,050 | Very loopy belief propagation for unwrapping phase images Brendan J . Freyl, Ralf Koetter2, Nemanja Petrovic1,2 1 Probabilistic and Statistical Inference Group, University of Toronto http://www.psi.toronto.edu 2 Electrical and Computer Engineering, University of Illinois at Urbana Abstract Since th... | 2001 | 53 |
2,051 | Modularity in the motor system: decomposition of muscle patterns as combinations of time-varying synergies Andrea d’Avella and Matthew C. Tresch Department of Brain and Cognitive Sciences Massachusetts Institute of Technology, E25-526 Cambridge, MA 02139 davel, mtresch @ai.mit.edu Abstract The q... | 2001 | 54 |
2,052 | The Method of Quantum Clustering David Horn and Assaf Gottlieb School of Physics and Astronomy Raymond and Beverly Sackler Faculty of Exact Sciences Tel Aviv University, Tel Aviv 69978, Israel Abstract We propose a novel clustering method that is an extension of ideas inherent to scale-space clustering and ... | 2001 | 55 |
2,053 | Generating velocity tuning by asymmetric recurrent connections Xiaohui Xie and Martin A. Giese Dept. of Brain and Cognitive Sciences and CBCL Massachusetts Institute of Technology Cambridge, MA 02139 Dept. for Cognitive Neurology, University Clinic T¨ubingen Max-Planck-Institute for Bi... | 2001 | 56 |
2,054 | Incremental Learning and Selective Sampling via Parametric Optimization Framework for SVM Shai Fine IBM T. J. Watson Research Center fshai@us.ibm.com Katya Scheinberg IBM T. J. Watson Research Center katyas@us.ibm.com Abstract We propose a framework based on a parametric quadratic programm... | 2001 | 57 |
2,055 | Bayesian Predictive Profiles with Applications to Retail Transaction Data Igor V. Cadez Information and Computer Science University of California Irvine, CA 92697-3425, U.S.A. icadez@ics.uci.edu Padhraic Smyth Information and Computer Science University of California Irvine, CA 92697-3425, U.S.A. s... | 2001 | 58 |
2,056 | A Rational Analysis of Cognitive Control in a Speeded Discrimination Task Michael C. Mozer , Michael D. Colagrosso , David E. Huber Department of Computer Science Department of Psychology Institute of Cognitive Science University of Colorado Boulder, CO 80309 mozer,colagro... | 2001 | 59 |
2,057 | Analysis of Sparse Bayesian Learning Anita C. Fanl Michael E. Tipping Microsoft Research St George House, 1 Guildhall St Cambridge CB2 3NH, U.K. Abstract The recent introduction of the 'relevance vector machine' has effectively demonstrated how sparsity may be obtained in generalised linear mode... | 2001 | 6 |
2,058 | Learning spike-based correlations and conditional probabilities in silicon Aaron P. Shon David Hsu Chris Diorio Department of Computer Science and Engineering University of Washington Seattle, WA 98195-2350 USA {aaron, hsud, diorio}@cs.washington.edu ... | 2001 | 60 |
2,059 | A Natural Policy Gradient Sham Kakade Gatsby Computational Neuroscience Unit 17 Queen Square, London, UK WC1N 3AR http://www.gatsby.ucl.ac.uk sham@gatsby.ucl.ac.uk Abstract We provide a natural gradient method that represents the steepest descent direction based on the underlying structure of th... | 2001 | 61 |
2,060 | Spectral Kernel Methods for Clustering N ello Cristianini BIOwulf Technologies nello@support-vector.net John Shawe-Taylor Jaz Kandola Royal Holloway, University of London {john, jaz} @cs.rhul.ac.uk Abstract In this paper we introduce new algorithms for unsupervised learning based on the use o... | 2001 | 62 |
2,061 | Batch Value Function Approximation via Support Vectors Thomas G Dietterich Department of Computet Science Oregon State University Corvallis, OR, 97331 tgd@cs.orst.edu Xin W"ang Department of Computer Science Oregon State University Corvallis, OR, 97331 wangxi@cs. orst. edu Abstract We present ... | 2001 | 63 |
2,062 | PAC Generalization Bounds for Co-training Sanjoy Dasgupta AT&T Labs–Research dasgupta@research.att.com Michael L. Littman AT&T Labs–Research mlittman@research.att.com David McAllester AT&T Labs–Research dmac@research.att.com Abstract The rule-based bootstrapping introduced by Yarowsky, and its cot... | 2001 | 64 |
2,063 | Face Recognition Using Kernel Methods Ming-Hsuan Yang Honda Fundamental Research Labs Mountain View, CA 94041 myang@hra.com Abstract Principal Component Analysis and Fisher Linear Discriminant methods have demonstrated their success in face detection, recognition, and tracking. The representation in these... | 2001 | 65 |
2,064 | Keywords: portfolio management, financial forecasting, recurrent neural networks. Active Portfolio-Management based on Error Correction Neural Networks Hans Georg Zimmermann , Ralph Neuneier and Ralph Grothmann Siemens AG Corporate Technology D-81730 M¨unchen, Germany Abstract This paper deals with a ... | 2001 | 66 |
2,065 | Generalization Performance of Some Learning Problems in Hilbert Functional Spaces Tong Zhang IBM T.J. Watson Research Center Yorktown Heights, NY 10598 tzhang@watson.ibm.com Abstract We investigate the generalization performance of some learning problems in Hilbert functional Spaces. We introduce a notion... | 2001 | 67 |
2,066 | Analog Soft-Pattern-Matching Classifier using Floating-Gate MOS Technology Toshihiko YAMASAKI and Tadashi SHIBATA* Department of Electronic Engineering, School of Engineering *Department of Frontier Informatics, School of Frontier Science The University of Tokyo 7-3-1 Hongo, Bunkyo-ku, Tokyo, ... | 2001 | 68 |
2,067 | Generalizable Relational Binding from Coarse-coded Distributed Representations Randall C. O’Reilly Department of Psychology University of Colorado Boulder 345 UCB Boulder, CO 80309 oreilly@psych.colorado.edu Richard S. Busby Department of Psychology University of Colorado Boulder 345 UCB Boulder... | 2001 | 69 |
2,068 | A hierarchical model of complex cells in visual cortex for the binocular perception of motion-in-depth Silvio P. Sabatini, Fabio Solari, Giulia Andreani, Chiara Bartolozzi, and Giacomo M. Bisio Department of Biophysical and Electronic Engineering University of Genoa, 1-16145 Genova, ITALY silvio@di... | 2001 | 7 |
2,069 | On the Concentration of Spectral Properties John Shawe-Taylor Royal Holloway, University of London john@cs.rhul.ac.uk Jaz Kandola N ella Cristianini BIOwulf Technologies nello@support-vector. net Royal Holloway, University of London jaz@cs.rhul.ac.uk Abstract We consider the problem ... | 2001 | 70 |
2,070 | Small-World Phenomena and the Dynamics of Information Jon Kleinberg Department of Computer Science Cornell University Ithaca NY 14853 1 Introduction The problem of searching for information in networks like the World Wide Web can be approached in a variety of ways, ranging from centralized indexing sc... | 2001 | 71 |
2,071 | Stochastic Mixed-Signal VLSI Architecture for High-Dimensional Kernel Machines Roman Genov and Gert Cauwenberghs Department of Electrical and Computer Engineering Johns Hopkins University, Baltimore, MD 21218 roman,gert @jhu.edu Abstract A mixed-signal paradigm is presented for high-resolution paral... | 2001 | 72 |
2,072 | The Emergence of Multiple Movement Units in the Presence of Noise and Feedback Delay Michael Kositsky Andrew G. Barto Department of Computer Science University of Massachusetts Amherst, MA 01003-4610 kositsky,barto @cs.umass.edu Abstract Tangential hand velocity profiles of rapid human arm moveme... | 2001 | 73 |
2,073 | Pranking with Ranking Koby Crammer and Yoram Singer School of Computer Science & Engineering The Hebrew University, Jerusalem 91904, Israel {kobics,singer}@cs.huji.ac.il Abstract We discuss the problem of ranking instances. In our framework each instance is associated with a rank or a rating,... | 2001 | 74 |
2,074 | Variance Reduction Techniques for Gradient Estimates in Reinforcement Learning Evan Greensmith Australian National University evan@csl.anu.edu.au Peter L. Bartlett∗ BIOwulf Technologies Peter.Bartlett@anu.edu.au Jonathan Baxter∗ WhizBang! Labs, East jbaxter@whizbang.com Abstract We consider the ... | 2001 | 75 |
2,075 | Asymptotic Universality for Learning Curves of Support Vector Machines M.Opperl R. Urbanczik2 1 Neural Computing Research Group School of Engineering and Applied Science Aston University, Birmingham B4 7ET, UK. opperm@aston.ac.uk 2Institut Fur Theoretische Physik, Universitiit Wurzburg Am Rub... | 2001 | 76 |
2,076 | Active Information Retrieval Tommi Jaakkola MIT AI Lab Cambridge, MA tommi@ai.mit.edu Abstract Hava Siegelmann MIT LIDS Cambridge, MA hava@mit.edu In classical large information retrieval systems, the system responds to a user initiated query with a list of results ranked by relevance. ... | 2001 | 77 |
2,077 | Tempo Tracking Rhythm by Sequential Monte Ali Taylan Ce:mgil and Bert Kappen SNN, University of Nijmegen NL 6525 EZ Nijmegen The Netherlands {cemgil,bert}@mbfys.kun.nl Abstract We present a probabilistic generative model for timing deviations in expressive music. performance. The structure of the pr... | 2001 | 78 |
2,078 | Learning a Gaussian Process Prior for Automatically Generating Music Playlists John C. Platt Christopher J. C. Burges Steven Swenson Christopher Weare Alice Zheng Microsoft Corporation 1 Microsoft Way Redmond, WA 98052 jplatt,cburges,sswenson,chriswea @microsoft.com, alicez@cs.berkeley.edu ... | 2001 | 79 |
2,079 | Motivated Reinforcement Learning Peter Dayan Gatsby Computational Neuroscience Unit 17 Queen Square, London, England, WClN 3AR. dayan@gatsby.ucl.ac.uk Abstract The standard reinforcement learning view of the involvement of neuromodulatory systems in instrumental conditioning includes a rather strai... | 2001 | 8 |
2,080 | Exact differential equation population dynamics for Integrate-and-Fire neurons Julian Eggert * HONDA R&D Europe (Deutschland) GmbH Future Technology Research Carl-Legien-StraBe 30 63073 Offenbach/Main, Germany julian. eggert@hre-ftr.f.rd.honda.co.jp Berthold Bauml Institut fur Robotik und Mec... | 2001 | 80 |
2,081 | Improvisation and Learning Judy A. Franklin Computer Science Department Smith College Northampton, MA 01063 jfranklin@cs.smith.edu Abstract This article presents a 2-phase computational learning model and application. As a demonstration, a system has been built, called CHIME for Computer Human Interact... | 2001 | 81 |
2,082 | Geometrical Singularities in the Neuromanifold of Multilayer Perceptrons Shun-ichi Amari, Hyeyoung Park, and Tomoko Ozeki Brain Science Institute, RIKEN Hirosawa 2-1, Wako, Saitama, 351-0198, Japan {amari, hypark, tomoko} @brain.riken.go.jp Abstract Singularities are ubiquitous in the parameter spa... | 2001 | 82 |
2,083 | A Sequence Kernel and its Application to Speaker Recognition William M. Campbell Motorola Human Interface Lab 7700 S. River Parkway Tempe, AZ 85284 Bill.Campbell@motorola.com Abstract A novel approach for comparing sequences of observations using an explicit-expansion kernel is demonstrated. The kerne... | 2001 | 83 |
2,084 | Convergence of Optimistic and Incremental Q-Learning Eyal Even-Dar* Abstract Yishay Mansourt Vie sho,v the convergence of tV/O deterministic variants of Qlearning. The first is the widely used optimistic Q-learning, which initializes the Q-values to large initial values and then follows a greedy policy wi... | 2001 | 84 |
2,085 | . Rao-Blackwellised Particle Filtering Data Augmentation VIa Christophe Andrieu Statistics Group University of Bristol University Walk Bristol BS8 1TW, UK C.Andrieu@bristol.ac.uk N ando de Freitas Computer Science UC Berkeley 387 Soda Hall, Berkeley CA 94720-1776, USA jfgf@c... | 2001 | 85 |
2,086 | Boosting and Maximum Likelihood for Exponential Models 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 We derive an eq... | 2001 | 86 |
2,087 | Iterative Double Clustering for Unsupervised and Semi-Supervised Learning Ran El-Yaniv Oren Souroujon Computer Science Department Technion - Israel Institute of Technology (rani,orenso)@cs.technion.ac.il Abstract We present a powerful meta-clustering technique called Iterative Double Clustering (IDC).... | 2001 | 87 |
2,088 | Multiagent Planning with Factored MDPs Carlos Guestrin Computer Science Dept Stanford University guestrin@cs.stanford.edu Daphne Koller Computer Science Dept Stanford University koller@cs.stanford.edu Ronald Parr Computer Science Dept Duke University parr@cs.duke.edu Abstract We present a pr... | 2001 | 88 |
2,089 | ACh, Uncertainty, and Cortical Inference Peter Dayan Angela Yu Gatsby Computational Neuroscience Unit 17 Queen Square, London, England, WC1N 3AR. dayan@gatsby.ucl.ac.uk feraina@gatsby.ucl.ac.uk Abstract Acetylcholine (ACh) has been implicated in a wide variety of tasks involving attentional processes ... | 2001 | 89 |
2,090 | Categorization by Learning and Combining Object Parts Bernd Heisele Thomas Serre Massimiliano Pontil Thomas Vetter Tomaso Poggio Center for Biological and Computational Learning, M.I.T., Cambridge, MA, USA Honda R&D Americas, Inc., Boston, MA, USA Department of Information Engin... | 2001 | 9 |
2,091 | On Discriminative vs. Generative classifiers: A comparison of logistic regression and naive Bayes Andrew Y. Ng Computer Science Division University of California, Berkeley Berkeley, CA 94720 Michael I. Jordan C.S. Div. & Dept. of Stat. University of California, Berkeley Berkeley, CA 94720 ... | 2001 | 90 |
2,092 | Risk Sensitive Particle Filters Sebastian Thrun, John Langford, Vandi Verma School of Computer Science Carnegie Mellon University Pittsburgh, PA 15213 thrun,jcl,vandi @cs.cmu.edu Abstract We propose a new particle filter that incorporates a model of costs when generating particles. The approach is ... | 2001 | 91 |
2,093 | Characterizing neural gain control using spike-triggered covariance Odelia Schwartz Center for Neural Science New York University odelia@cns.nyu.edu E. J. Chichilnisky Systems Neurobiology The Salk Institute ej@salk.edu Eero P. Simoncelli Howard Hughes Medical Inst. Center for Neural Science N... | 2001 | 92 |
2,094 | Speech Recognition with Missing Data using Recurrent Neural Nets P.D. Green Speech and Hearing Research Group Department of Computer Science University of Sheffield Sheffield S14DP, UK p.green@dcs.shef.ac.uk S. Parveen Speech and Hearing Research Group Department of Computer Science University of Sh... | 2001 | 93 |
2,095 | On Spectral Clustering: Analysis and an algorithm Andrew Y. Ng CS Division U.C. Berkeley ang@cs.berkeley.edu Michael I. Jordan CS Div. & Dept. of Stat. U.C. Berkeley jordan@cs.berkeley.edu Abstract Yair Weiss School of CS & Engr. The Hebrew Univ. yweiss@cs.huji.ac.il Despite... | 2001 | 94 |
2,096 | Grouping with Bias Stella X. Yu Robotics Institute Carnegie Mellon University Center for the Neural Basis of Cognition Pittsburgh, PA 15213-3890 stella. yu@es. emu. edu Abstract Jianbo Shi Robotics Institute Carnegie Mellon University 5000 Forbes Ave Pittsburgh, PA 15213-3890 jshi@es.emu.edu ... | 2001 | 95 |
2,097 | Learning hierarchical structures with Linear Relational Embedding Alberto Paccanaro Geoffrey E. Hinton Gatsby Computational Neuroscience Unit UCL, 17 Queen Square, London, UK alberto,hinton @gatsby.ucl.ac.uk Abstract We present Linear Relational Embedding (LRE), a new method of learning a distribu... | 2001 | 96 |
2,098 | Constructing Distributed Representations Using Additive Clustering Wheeler Ruml Division of Engineering and Applied Sciences Harvard University 33 Oxford Street, Cambridge, MA 02138 ruml@eecs.harvard.edu Abstract If the promise of computational modeling is to be fully realized in higherlevel cognitive d... | 2001 | 97 |
2,099 | Products of Gaussians Christopher K. I. Williams Division of Informatics University of Edinburgh Edinburgh EH1 2QL, UK c.k. i. williams@ed.ac.uk http://anc.ed.ac.uk Felix V. Agakov System Engineering Research Group Chair of Manufacturing Technology Universitiit Erlangen-Niirnberg 91058 ... | 2001 | 98 |
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