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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2,500 | Gaussian Processes in Reinforcement Learning Carl Edward Rasmussen and Malte Kuss Max Planck Institute for Biological Cybernetics Spemannstraße 38, 72076 T¨ubingen, Germany carl,malte.kuss @tuebingen.mpg.de Abstract We exploit some useful properties of Gaussian process (GP) regression models for rei... | 2003 | 94 |
2,501 | The doubly balanced network of spiking neurons: a memory model with high capacity Yuval Aviel* David Horn Interdisciplinary Center for Neural Computation School of Physics Hebrew University Tel Aviv University Jerusalem, Israel 91904 Tel Aviv, Israel 69978 ... | 2003 | 95 |
2,502 | Hierarchical Topic Models and the Nested Chinese Restaurant Process David M. Blei Thomas L. Griffiths blei@cs.berkeley.edu gruffydd@mit.edu Michael I. Jordan Joshua B. Tenenbaum jordan@cs.berkeley.edu jbt@mit.edu University of California, Berkeley Massachusetts Institute of Technology Berkeley, C... | 2003 | 96 |
2,503 | A Sampled Texture Prior for Image Super-Resolution Lyndsey C. Pickup, Stephen J. Roberts and Andrew Zisserman Robotics Research Group Department of Engineering Science University of Oxford Parks Road, Oxford, OX1 3PJ {elle,sjrob,az}@robots.ox.ac.uk Abstract Super-resolution aims to produce a high-reso... | 2003 | 97 |
2,504 | Analytical solution of spike-timing dependent plasticity based on synaptic biophysics Bernd Porr, Ausra Saudargiene and Florentin W¨org¨otter Computational Neuroscience Psychology University of Stirling FK9 4LR Stirling, UK {Bernd.Porr,ausra,worgott}@cn.stir.ac.uk Abstract Spike timing plasticity (STD... | 2003 | 98 |
2,505 | Sparse Greedy Minimax Probability Machine Classification Thomas R. Strohmann Department of Computer Science University of Colorado, Boulder strohman@cs.colorado.edu Andrei Belitski Department of Computer Science University of Colorado, Boulder Andrei.Belitski@colorado.edu Gregory Z. Grudic Departme... | 2003 | 99 |
2,506 | PAC-Bayes Learning of Conjunctions and Classification of Gene-Expression Data Mario Marchand IFT-GLO, Universit´e Laval Sainte-Foy (QC) Canada, G1K-7P4 Mario.Marchand@ift.ulaval.ca Mohak Shah SITE, University of Ottawa Ottawa, Ont. Canada,K1N-6N5 mshah@site.uottawa.ca Abstract We propose a “soft gr... | 2004 | 1 |
2,507 | A Probabilistic Model for Online Document Clustering with Application to Novelty Detection Jian Zhang† †School of Computer Science Cargenie Mellon University Pittsburgh, PA 15213 jian.zhang@cs.cmu.edu Zoubin Ghahramani†‡ ‡ Gatsby Computational Neuroscience Unit University College London London WC1N ... | 2004 | 10 |
2,508 | VDCBPI: an Approximate Scalable Algorithm for Large POMDPs Pascal Poupart Department of Computer Science University of Toronto Toronto, ON M5S 3H5 ppoupart@cs.toronto.edu Craig Boutilier Department of Computer Science University of Toronto Toronto, ON M5S 3H5 cebly@cs.toronto.edu Abstract Exis... | 2004 | 100 |
2,509 | A Generalized Bradley-Terry Model: From Group Competition to Individual Skill Tzu-Kuo Huang Chih-Jen Lin Department of Computer Science National Taiwan University Taipei 106, Taiwan Ruby C. Weng Department of Statistics National Chenechi University Taipei 116, Taiwan Abstract The Bradley-Terry m... | 2004 | 101 |
2,510 | Rate- and Phase-coded Autoassociative Memory Máté Lengyel Peter Dayan Gatsby Computational Neuroscience Unit, University College London 17 Queen Square, London WC1N 3AR, United Kingdom {lmate,dayan}@gatsby.ucl.ac.uk Abstract Areas of the brain involved in various forms of memory exhibit patterns of neur... | 2004 | 102 |
2,511 | Constraining a Bayesian Model of Human Visual Speed Perception Alan A. Stocker and Eero P. Simoncelli Howard Hughes Medical Institute, Center for Neural Science, and Courant Institute of Mathematical Sciences New York University, U.S.A. Abstract It has been demonstrated that basic aspects of human visual ... | 2004 | 103 |
2,512 | Efficient Kernel Machines Using the Improved Fast Gauss Transform Changjiang Yang, Ramani Duraiswami and Larry Davis Department of Computer Science, Perceptual Interfaces and Reality Laboratory University of Maryland, College Park, MD 20742 {yangcj,ramani,lsd}@umiacs.umd.edu Abstract The computation and me... | 2004 | 104 |
2,513 | Responding to modalities with different latencies Fredrik Bissmarck Computational Neuroscience Labs ATR International Hikari-dai 2-2-2, Seika, Soraku Kyoto 619-0288 JAPAN xfredrik@atr.jp Hiroyuki Nakahara Laboratory for Mathematical Neuroscience RIKEN Brain Science Institute Hirosawa 2-1-1, Wako S... | 2004 | 105 |
2,514 | Two-Dimensional Linear Discriminant Analysis Jieping Ye Department of CSE University of Minnesota jieping@cs.umn.edu Ravi Janardan Department of CSE University of Minnesota janardan@cs.umn.edu Qi Li Department of CIS University of Delaware qili@cis.udel.edu Abstract Linear Discriminant Analy... | 2004 | 106 |
2,515 | Assignment of Multiplicative Mixtures in Natural Images Odelia Schwartz HHMI and Salk Institute La Jolla, CA 92014 odelia@salk.edu Terrence J. Sejnowski HHMI and Salk Institute La Jolla, CA 92014 terry@salk.edu Peter Dayan GCNU, UCL 17 Queen Square, London dayan@gatsby.ucl.ac.uk Abstract I... | 2004 | 107 |
2,516 | Convergence and No-Regret in Multiagent Learning Michael Bowling Department of Computing Science University of Alberta Edmonton, Alberta Canada T6G 2E8 bowling@cs.ualberta.ca Abstract Learning in a multiagent system is a challenging problem due to two key factors. First, if other agents are simultan... | 2004 | 108 |
2,517 | Learning efficient auditory codes using spikes predicts cochlear filters Evan Smith1 evan@cnbc.cmu.edu Michael S. Lewicki2 lewicki@cnbc.cmu.edu Departments of Psychology1 & Computer Science2 Center for the Neural Basis of Cognition Carnegie Mellon University Abstract The representation of acoustic sig... | 2004 | 109 |
2,518 | Non-Local Manifold Tangent Learning Yoshua Bengio and Martin Monperrus Dept. IRO, Universit´e de Montr´eal P.O. Box 6128, Downtown Branch, Montreal, H3C 3J7, Qc, Canada {bengioy,monperrm}@iro.umontreal.ca Abstract We claim and present arguments to the effect that a large class of manifold learning algorithm... | 2004 | 11 |
2,519 | Active Learning for Anomaly and Rare-Category Detection 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 introduce a novel active-learning scenario in which a user wants to work with a learning alg... | 2004 | 110 |
2,520 | A feature selection algorithm based on the global minimization of a generalization error bound Dori Peleg Department of Electrical Engineering Technion Haifa, Israel dorip@tx.technion.ac.il Ron Meir Department of Electrical Engineering Technion Haifa, Israel rmeir@tx.technion.ac.il Abstract A ... | 2004 | 111 |
2,521 | Semi-supervised Learning with Penalized Probabilistic Clustering Zhengdong Lu and Todd K. Leen Department of Computer Science and Engineering OGI School of Science and Engineering , OHSU Beaverton, OR 97006 {zhengdon,tleen}@cse.ogi.edu Abstract While clustering is usually an unsupervised operation, ther... | 2004 | 112 |
2,522 | A direct formulation for sparse PCA using semidefinite programming Alexandre d’Aspremont EECS Dept. U.C. Berkeley Berkeley, CA 94720 alexandre.daspremont@m4x.org Laurent El Ghaoui SAC Capital 540 Madison Avenue New York, NY 10029 laurent.elghaoui@sac.com (on leave from EECS, U.C. Berkeley) Mich... | 2004 | 113 |
2,523 | Stable adaptive control with online learning Andrew Y. Ng Stanford University Stanford, CA 94305, USA H. Jin Kim Seoul National University Seoul, Korea Abstract Learning algorithms have enjoyed numerous successes in robotic control tasks. In problems with time-varying dynamics, online learning methods... | 2004 | 114 |
2,524 | The Rescorla-Wagner algorithm and Maximum Likelihood estimation of causal parameters. Alan Yuille Department of Statistics University of California at Los Angeles Los Angeles, CA 90095 yuille@stat.ucla.edu Abstract This paper analyzes generalization of the classic Rescorla-Wagner (RW) learning algorithm... | 2004 | 115 |
2,525 | Contextual models for object detection using boosted random fields Antonio Torralba MIT, CSAIL Cambridge, MA 02139 torralba@mit.edu Kevin P. Murphy UBC, CS Vancouver, BC V6T 1Z4 murphyk@cs.ubc.edu William T. Freeman MIT, CSAIL Cambridge, MA 02139 billf@mit.edu Abstract We seek to both detec... | 2004 | 116 |
2,526 | An Auditory Paradigm for Brain–Computer Interfaces N. Jeremy Hill1, T. Navin Lal1, Karin Bierig1 Niels Birbaumer2 and Bernhard Sch¨olkopf1 1Max Planck Institute for Biological Cybernetics, Spemannstraße 38, 72076 T¨ubingen, Germany. {jez|navin|bierig|bs}@tuebingen.mpg.de 2Institute for Medical Psychology ... | 2004 | 117 |
2,527 | Worst-Case Analysis of Selective Sampling for Linear-Threshold Algorithms∗ Nicol`o Cesa-Bianchi DSI, University of Milan cesa-bianchi@dsi.unimi.it Claudio Gentile Universit`a dell’Insubria gentile@dsi.unimi.it Luca Zaniboni DTI, University of Milan zaniboni@dti.unimi.it Abstract We provide a wor... | 2004 | 118 |
2,528 | Markov Networks for Detecting Overlapping Elements in Sequence Data Joseph Bockhorst Dept. of Computer Sciences University of Wisconsin Madison, WI 53706 joebock@cs.wisc.edu Mark Craven Dept. of Biostatistics and Medical Informatics University of Wisconsin Madison, WI 53706 craven@biostat.wisc.edu... | 2004 | 119 |
2,529 | Maximal Margin Labeling for Multi-Topic Text Categorization Hideto Kazawa, Tomonori Izumitani, Hirotoshi Taira and Eisaku Maeda NTT Communication Science Laboratories Nippon Telegraph and Telephone Corporation 2-4 Hikaridai, Seikacho, Sorakugun, Kyoto 619-0237 Japan {kazawa,izumi,taira,maeda}@cslab.kecl.ntt... | 2004 | 12 |
2,530 | Co-Validation: Using Model Disagreement on Unlabeled Data to Validate Classification Algorithms Omid Madani, David M. Pennock, Gary W. Flake Yahoo! Research Labs 3rd floor, Pasadena Ave. Pasadena, CA 91103 {madani|pennockd|flakeg}@yahoo-inc.com Abstract In the context of binary classification, we define di... | 2004 | 120 |
2,531 | Co-Training and Expansion: Towards Bridging Theory and Practice Maria-Florina Balcan Computer Science Dept. Carnegie Mellon Univ. Pittsburgh, PA 15213 ninamf@cs.cmu.edu Avrim Blum Computer Science Dept. Carnegie Mellon Univ. Pittsburgh, PA 15213 avrim@cs.cmu.edu Ke Yang Computer Science Dept. ... | 2004 | 121 |
2,532 | Probabilistic Inference of Alternative Splicing Events in Microarray Data Ofer Shai, Brendan J. Frey, and Quaid D. Morris Dept. of Electrical & Computer Engineering University of Toronto, Toronto, ON Qun Pan, Christine Misquitta, and Benjamin J. Blencowe Banting & Best Dept. of Medical Research University... | 2004 | 122 |
2,533 | Semi-supervised Learning by Entropy Minimization Yves Grandvalet ∗ Heudiasyc, CNRS/UTC 60205 Compi`egne cedex, France grandval@utc.fr Yoshua Bengio Dept. IRO, Universit´e de Montr´eal Montreal, Qc, H3C 3J7, Canada bengioy@iro.umontreal.ca Abstract We consider the semi-supervised learning problem, ... | 2004 | 123 |
2,534 | Detecting Significant Multidimensional Spatial Clusters Daniel B. Neill, Andrew W. Moore, Francisco Pereira, and Tom Mitchell School of Computer Science Carnegie Mellon University Pittsburgh, PA 15213 {neill,awm,fpereira,t.mitchell}@cs.cmu.edu Abstract Assume a uniform, multidimensional grid of bivariate... | 2004 | 124 |
2,535 | Message Errors in Belief Propagation Alexander T. Ihler, John W. Fisher III, and Alan S. Willsky Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology ihler@mit.edu, fisher@csail.mit.edu, willsky@mit.edu Abstract Belief propagation (BP) is an increasingly popular met... | 2004 | 125 |
2,536 | Methods Towards Invasive Human Brain Computer Interfaces Thomas Navin Lal1, Thilo Hinterberger2, Guido Widman3, Michael Schr¨oder4, Jeremy Hill1, Wolfgang Rosenstiel4, Christian E. Elger3, Bernhard Sch¨olkopf1 and Niels Birbaumer2,5 1 Max-Planck-Institute for Biological Cybernetics, T¨ubingen, Germany {navi... | 2004 | 126 |
2,537 | A Three Tiered Approach for Articulated Object Action Modeling and Recognition Le Lu Gregory D. Hager Department of Computer Science Johns Hopkins University Baltimore, MD 21218 lelu/hager@cs.jhu.edu Laurent Younes Center of Imaging Science Johns Hopkins University Baltimore, MD 21218 younes@cis... | 2004 | 127 |
2,538 | Temporal-Difference Networks Richard S. Sutton and Brian Tanner Department of Computing Science University of Alberta Edmonton, Alberta, Canada T6G 2E8 {sutton,btanner}@cs.ualberta.ca Abstract We introduce a generalization of temporal-difference (TD) learning to networks of interrelated predictions. Rat... | 2004 | 128 |
2,539 | Methods for Estimating the Computational Power and Generalization Capability of Neural Microcircuits Wolfgang Maass, Robert Legenstein, Nils Bertschinger Institute for Theoretical Computer Science Technische Universit¨at Graz A-8010 Graz, Austria {maass, legi, nilsb}@igi.tugraz.at Abstract What makes ... | 2004 | 129 |
2,540 | Conditional Random Fields for Object Recognition Ariadna Quattoni Michael Collins Trevor Darrell MIT Computer Science and Artificial Intelligence Laboratory Cambridge, MA 02139 {ariadna, mcollins, trevor}@csail.mit.edu Abstract We present a discriminative part-based approach for the recognition of ob... | 2004 | 13 |
2,541 | The Variational Ising Classifier (VIC) algorithm for coherently contaminated data Oliver Williams Dept. of Engineering University of Cambridge omcw2@cam.ac.uk Andrew Blake Microsoft Research Ltd. Cambridge, UK Roberto Cipolla Dept. of Engineering University of Cambridge Abstract There has been ... | 2004 | 130 |
2,542 | Generalization Error and Algorithmic Convergence of Median Boosting Bal´azs K´egl Department of Computer Science and Operations Research, University of Montreal CP 6128 succ. Centre-Ville, Montr´eal, Canada H3C 3J7 kegl@iro.umontreal.ca Abstract We have recently proposed an extension of ADABOOST to regres... | 2004 | 131 |
2,543 | Supervised graph inference Jean-Philippe Vert Centre de G´eostatistique Ecole des Mines de Paris 35 rue Saint-Honor´e 77300 Fontainebleau, France Jean-Philippe.Vert@mines.org Yoshihiro Yamanishi Bioinformatics Center Institute for Chemical Research Kyoto University Uji, Kyoto 611-0011, Japan yos... | 2004 | 132 |
2,544 | Confidence Intervals for the Area under the ROC Curve Corinna Cortes Google Research 1440 Broadway New York, NY 10018 corinna@google.com Mehryar Mohri Courant Institute, NYU 719 Broadway New York, NY 10003 mohri@cs.nyu.edu Abstract In many applications, good ranking is a highly desirable perfor... | 2004 | 133 |
2,545 | Maximising Sensitivity in a Spiking Network Anthony J. Bell, Redwood Neuroscience Institute 1010 El Camino Real, Suite 380 Menlo Park, CA 94025 tbell@rni.org Lucas C. Parra Biomedical Engineering Department City College of New York New York, NY 10033 parra@ccny.cuny.edu Abstract We use unsupervi... | 2004 | 134 |
2,546 | Probabilistic computation in spiking populations Richard S. Zemel Dept. of Comp. Sci. Univ. of Toronto Quentin J. M. Huys Gatsby CNU UCL Rama Natarajan Dept. of Comp. Sci. Univ. of Toronto Peter Dayan Gatsby CNU UCL Abstract As animals interact with their environments, they must constantly u... | 2004 | 135 |
2,547 | Theory of Localized Synfire Chain: Characteristic Propagation Speed of Stable Spike Patterns Kosuke Hamaguchi RIKEN Brain Science Institute Wako, Saitama 351-0198, JAPAN hammer@brain.riken.jp Masato Okada Dept. of Complexity Science and Engineering, University of Tokyo, Kashiwa, Chiba, 277-8561, JAPA... | 2004 | 136 |
2,548 | Semi-supervised Learning on Directed Graphs Dengyong Zhou†, Bernhard Sch¨olkopf†, and Thomas Hofmann‡† †Max Planck Institute for Biological Cybernetics 72076 Tuebingen, Germany {dengyong.zhou, bernhard.schoelkopf}@tuebingen.mpg.de ‡Department of Computer Science, Brown University Providence, RI 02912 USA ... | 2004 | 137 |
2,549 | Class-size Independent Generalization Analsysis of Some Discriminative Multi-Category Classification Methods Tong Zhang IBM T.J. Watson Research Center Yorktown Heights, NY 10598 tzhang@watson.ibm.com Abstract We consider the problem of deriving class-size independent generalization bounds for some regul... | 2004 | 138 |
2,550 | ℓ0-norm Minimization for Basis Selection David Wipf and Bhaskar Rao ∗ Department of Electrical and Computer Engineering University of California, San Diego, CA 92092 dwipf@ucsd.edu, brao@ece.ucsd.edu Abstract Finding the sparsest, or minimum ℓ0-norm, representation of a signal given an overcomplete dict... | 2004 | 139 |
2,551 | Inference, Attention, and Decision in a Bayesian Neural Architecture Angela J. Yu Peter Dayan Gatsby Computational Neuroscience Unit, UCL 17 Queen Square, London WC1N 3AR, United Kingdom. feraina@gatsby.ucl.ac.uk dayan@gatsby.ucl.ac.uk Abstract We study the synthesis of neural coding, selective attent... | 2004 | 14 |
2,552 | The Power of Selective Memory: Self-Bounded Learning of Prediction Suffix Trees Ofer Dekel Shai Shalev-Shwartz Yoram Singer School of Computer Science & Engineering The Hebrew University, Jerusalem 91904, Israel {oferd,shais,singer}@cs.huji.ac.il Abstract Prediction suffix trees (PST) provide a popular ... | 2004 | 140 |
2,553 | Modelling Uncertainty in the Game of Go David H. Stern Department of Physics Cambridge University dhs26@cam.ac.uk Thore Graepel Microsoft Research Cambridge, U.K. thoreg@microsoft.com David J. C. MacKay Department of Physics Cambridge University mackay@mrao.cam.ac.uk Abstract Go is an ancien... | 2004 | 141 |
2,554 | Spike Sorting: Bayesian Clustering of Non-Stationary Data Aharon Bar-Hillel Neural Computation Center The Hebrew University of Jerusalem aharonbh@cs.huji.ac.il Adam Spiro School of Computer Science and Engineering The Hebrew University of Jerusalem adams@cs.huji.ac.il Eran Stark Department of Phys... | 2004 | 142 |
2,555 | Harmonising Chorales by Probabilistic Inference Moray Allan and Christopher K. I. Williams School of Informatics, University of Edinburgh Edinburgh EH1 2QL moray.allan@ed.ac.uk, c.k.i.williams@ed.ac.uk Abstract We describe how we used a data set of chorale harmonisations composed by Johann Sebastian Bach ... | 2004 | 143 |
2,556 | Nearly Tight Bounds for the Continuum-Armed Bandit Problem Robert Kleinberg∗ Abstract In the multi-armed bandit problem, an online algorithm must choose from a set of strategies in a sequence of n trials so as to minimize the total cost of the chosen strategies. While nearly tight upper and lower bounds a... | 2004 | 144 |
2,557 | Mistake Bounds for Maximum Entropy Discrimination Philip M. Long Center for Computational Learning Systems Columbia University plong@cs.columbia.edu Xinyu Wu Department of Computer Science National University of Singapore wuxy@comp.nus.edu.sg Abstract We establish a mistake bound for an ensemble m... | 2004 | 145 |
2,558 | A harmonic excitation state-space approach to blind separation of speech Rasmus Kongsgaard Olsson and Lars Kai Hansen Informatics and Mathematical Modelling Technical University of Denmark, 2800 Lyngby, Denmark rko,lkh@imm.dtu.dk Abstract We discuss an identification framework for noisy speech mixtures. A ... | 2004 | 146 |
2,559 | Matrix Exponentiated Gradient Updates for On-line Learning and Bregman Projection Koji Tsuda∗†, Gunnar R¨atsch∗‡and Manfred K. Warmuth§ ∗Max Planck Institute for Biological Cybernetics Spemannstr. 38, 72076 T¨ubingen, Germany †AIST CBRC, 2-43 Aomi, Koto-ku, Tokyo, 135-0064, Japan ‡Fraunhofer FIRST, Kekul´es... | 2004 | 147 |
2,560 | Blind one-microphone speech separation: A spectral learning approach Francis R. Bach Computer Science 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 ... | 2004 | 148 |
2,561 | Resolving Perceptual Aliasing In The Presence Of Noisy Sensors∗ Ronen I. Brafman & Guy Shani Department of Computer Science Ben-Gurion University Beer-Sheva 84105, Israel {brafman, shanigu}@cs.bgu.ac.il Abstract Agents learning to act in a partially observable domain may need to overcome the problem o... | 2004 | 149 |
2,562 | Exponential Family Harmoniums with an Application to Information Retrieval Max Welling & Michal Rosen-Zvi Information and Computer Science University of California Irvine CA 92697-3425 USA welling@ics.uci.edu Geoffrey Hinton Department of Computer Science University of Toronto Toronto, 290G M5S 3G4,... | 2004 | 15 |
2,563 | Kernels for Multi–task Learning Charles A. Micchelli Department of Mathematics and Statistics State University of New York, The University at Albany 1400 Washington Avenue, Albany, NY, 12222, USA Massimiliano Pontil Department of Computer Sciences University College London Gower Street, London WC1E 6B... | 2004 | 150 |
2,564 | Variational minimax estimation of discrete distributions under KL loss Liam Paninski Gatsby Computational Neuroscience Unit University College London liam@gatsby.ucl.ac.uk http://www.gatsby.ucl.ac.uk/∼liam Abstract We develop a family of upper and lower bounds on the worst-case expected KL loss for esti... | 2004 | 151 |
2,565 | Online Bounds for Bayesian Algorithms Sham M. Kakade Computer and Information Science Department University of Pennsylvania Andrew Y. Ng Computer Science Department Stanford University Abstract We present a competitive analysis of Bayesian learning algorithms in the online learning setting and show th... | 2004 | 152 |
2,566 | Analysis of a greedy active learning strategy Sanjoy Dasgupta∗ University of California, San Diego dasgupta@cs.ucsd.edu Abstract We abstract out the core search problem of active learning schemes, to better understand the extent to which adaptive labeling can improve sample complexity. We give various upper... | 2004 | 153 |
2,567 | A Cost-Shaping LP for Bellman Error Minimization with Performance Guarantees Daniela Pucci de Farias Mechanical Engineering Massachusetts Institute of Technology Benjamin Van Roy Management Science and Engineering and Electrical Engineering Stanford University Abstract We introduce a new algorithm... | 2004 | 154 |
2,568 | Validity estimates for loopy Belief Propagation on binary real-world networks Joris Mooij Dept. of Biophysics, Inst. for Neuroscience, Radboud Univ. Nijmegen 6525 EZ Nijmegen, the Netherlands j.mooij@science.ru.nl Hilbert J. Kappen Dept. of Biophysics, Inst. for Neuroscience, Radboud Univ. Nijmegen 6525... | 2004 | 155 |
2,569 | Bayesian inference in spiking neurons Sophie Deneve∗ Gatsby Computational Neuroscience Unit University College London London, UK WC1N 3AR sdeneve@gatsby.ucl.ac.uk Abstract We propose a new interpretation of spiking neurons as Bayesian integrators accumulating evidence over time about events in the externa... | 2004 | 156 |
2,570 | Computing regularization paths for learning multiple kernels Francis R. Bach & Romain Thibaux Computer Science University of California Berkeley, CA 94720 {fbach,thibaux}@cs.berkeley.edu Michael I. Jordan Computer Science and Statistics University of California Berkeley, CA 94720 jordan@cs.berkele... | 2004 | 157 |
2,571 | Saliency-Driven Image Acuity Modulation on a Reconfigurable Silicon Array of Spiking Neurons R. Jacob Vogelstein1, Udayan Mallik2, Eugenio Culurciello3, Gert Cauwenberghs2 and Ralph Etienne-Cummings2 1Dept. of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 2Dept. of Electrical & Computer Engin... | 2004 | 158 |
2,572 | Common-Frame Model for Object Recognition Pierre Moreels Pietro Perona California Insitute of Technology - Pasadena CA91125 - USA pmoreels,perona@vision.caltech.edu Abstract A generative probabilistic model for objects in images is presented. An object consists of a constellation of features. Feature appe... | 2004 | 159 |
2,573 | Distributed Occlusion Reasoning for Tracking with Nonparametric Belief Propagation Erik B. Sudderth, Michael I. Mandel, William T. Freeman, and Alan S. Willsky Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology esuddert@mit.edu, mim@alum.mit.edu, billf@mit.edu, wil... | 2004 | 16 |
2,574 | Brain Inspired Reinforcement Learning François Rivest* Yoshua Bengio Département d’informatique et de recherche opérationnelle Université de Montréal CP 6128 succ. Centre Ville, Montréal, QC H3C 3J7, Canada francois.rivest@mail.mcgill.ca bengioy@iro.umontreal.ca ... | 2004 | 160 |
2,575 | Semi-supervised Learning via Gaussian Processes Neil D. Lawrence Department of Computer Science University of Sheffield Sheffield, S1 4DP, U.K. neil@dcs.shef.ac.uk Michael I. Jordan Computer Science and Statistics University of California Berkeley, CA 94720, U.S.A. jordan@cs.berkeley.edu Abstract ... | 2004 | 161 |
2,576 | Parallel Support Vector Machines: The Cascade SVM Hans Peter Graf, Eric Cosatto, Leon Bottou, Igor Durdanovic, Vladimir Vapnik NEC Laboratories 4 Independence Way, Princeton, NJ 08540 {hpg, cosatto, leonb, igord, vlad}@nec-labs.com Abstract We describe an algorithm for support v... | 2004 | 162 |
2,577 | Sampling Methods for Unsupervised Learning Rob Fergus∗& Andrew Zisserman Dept. of Engineering Science University of Oxford Parks Road, Oxford OX1 3PJ, UK. {fergus,az }@robots.ox.ac.uk Pietro Perona Dept. Electrical Engineering California Institute of Technology Pasadena, CA 91125, USA. perona@visi... | 2004 | 163 |
2,578 | Limits of Spectral Clustering Ulrike von Luxburg and Olivier Bousquet Max Planck Institute for Biological Cybernetics Spemannstr. 38, 72076 T¨ubingen, Germany {ulrike.luxburg,olivier.bousquet}@tuebingen.mpg.de Mikhail Belkin The University of Chicago, Department of Computer Science 1100 E 58th st., Ch... | 2004 | 164 |
2,579 | Using the Equivalent Kernel to Understand Gaussian Process Regression Peter Sollich Dept of Mathematics King’s College London Strand, London WC2R 2LS, UK peter.sollich@kcl.ac.uk Christopher K. I. Williams School of Informatics University of Edinburgh 5 Forrest Hill, Edinburgh EH1 2QL, UK c.k.i.wil... | 2004 | 165 |
2,580 | Newscast EM Wojtek Kowalczyk Department of Computer Science Vrije Universiteit Amsterdam The Netherlands wojtek@cs.vu.nl Nikos Vlassis Informatics Institute University of Amsterdam The Netherlands vlassis@science.uva.nl Abstract We propose a gossip-based distributed algorithm for Gaussian mixtur... | 2004 | 166 |
2,581 | Dynamic Bayesian Networks for Brain-Computer Interfaces Pradeep Shenoy Department of Computer Science University of Washington Seattle, WA 98195 pshenoy@cs.washington.edu Rajesh P. N. Rao Department of Computer Science University of Washington Seattle, WA 98195 rao@cs.washington.edu Abstract W... | 2004 | 167 |
2,582 | Edge of Chaos Computation in Mixed-Mode VLSI - “A Hard Liquid” Felix Sch¨urmann, Karlheinz Meier, Johannes Schemmel KirchhoffInstitute for Physics University of Heidelberg Im Neuenheimer Feld 227, 69120 Heidelberg, Germany felix.schuermann@kip.uni-heidelberg.de, WWW home page: http://www.kip.uni-heidelberg... | 2004 | 168 |
2,583 | Breaking SVM Complexity with Cross-Training G¨okhan H. Bakır Max Planck Institute for Biological Cybernetics, T¨ubingen, Germany gb@tuebingen.mpg.de L´eon Bottou NEC Labs America Princeton NJ, USA leon@bottou.org Jason Weston NEC Labs America Princeton NJ, USA jasonw@nec-labs.com Abstract ... | 2004 | 169 |
2,584 | An Investigation of Practical Approximate Nearest Neighbor Algorithms Ting Liu, Andrew W. Moore, Alexander Gray and Ke Yang School of Computer Science Carnegie-Mellon University Pittsburgh, PA 15213 USA {tingliu, awm, agray, yangke}@cs.cmu.edu Abstract This paper concerns approximate nearest neighbor se... | 2004 | 17 |
2,585 | Linear Multilayer Independent Component Analysis for Large Natural Scenes Yoshitatsu Matsuda ∗ Kazunori Yamaguchi Laboratory Department of General Systems Studies Graduate School of Arts and Sciences The University of Tokyo Japan 153-8902 matsuda@graco.c.u-tokyo.ac.jp Kazunori Yamaguchi yamaguch@gra... | 2004 | 170 |
2,586 | Identifying protein-protein interaction sites on a genome-wide scale Haidong Wang∗Eran Segal≀Asa Ben-Hur† Daphne Koller∗Douglas L. Brutlag‡ ∗Computer Science Department, Stanford University, CA 94305 {haidong, koller}@cs.stanford.edu ≀Center for Studies in Physics and Biology, Rockefeller University, NY 10021... | 2004 | 171 |
2,587 | Proximity graphs for clustering and manifold learning Miguel ´A. Carreira-Perpi˜n´an Richard S. Zemel Dept. of Computer Science, University of Toronto 6 King’s College Road. Toronto, ON M5S 3H5, Canada Email: {miguel,zemel}@cs.toronto.edu Abstract Many machine learning algorithms for clustering or dim... | 2004 | 172 |
2,588 | Fast Rates to Bayes for Kernel Methods Ingo Steinwart∗and Clint Scovel Modeling, Algorithms and Informatics Group, CCS-3 Los Alamos National Laboratory {ingo,jcs}@lanl.gov Abstract We establish learning rates to the Bayes risk for support vector machines (SVMs) with hinge loss. In particular, for SVMs wit... | 2004 | 173 |
2,589 | Discriminant Saliency for Visual Recognition from Cluttered Scenes Dashan Gao Nuno Vasconcelos Department of Electrical and Computer Engineering, University of California, San Diego Abstract Saliency mechanisms play an important role when visual recognition must be performed in cluttered scenes. We prop... | 2004 | 174 |
2,590 | Bayesian Regularization and Nonnegative Deconvolution for Time Delay Estimation Yuanqing Lin, Daniel D. Lee GRASP Laboratory, Department of Electrical and System Engineering University of Pennsylvania, Philadelphia, PA 19104 linyuanq, ddlee@seas.upenn.edu Abstract Bayesian Regularization and Nonnegative D... | 2004 | 175 |
2,591 | Algebraic Set Kernels with Application to Inference Over Local Image Representations Amnon Shashua and Tamir Hazan ∗ Abstract This paper presents a general family of algebraic positive definite similarity functions over spaces of matrices with varying column rank. The columns can represent local regions in an ... | 2004 | 176 |
2,592 | The Correlated Correspondence Algorithm for Unsupervised Registration of Nonrigid Surfaces Dragomir Anguelov1, Praveen Srinivasan1, Hoi-Cheung Pang1, Daphne Koller1, Sebastian Thrun1, James Davis2 ∗ 1 Stanford University, Stanford, CA 94305 2 University of California, Santa Cruz, CA 95064 e-mail:{drago,prav... | 2004 | 177 |
2,593 | Maximum-Margin Matrix Factorization Nathan Srebro Dept. of Computer Science University of Toronto Toronto, ON, CANADA nati@cs.toronto.edu Jason D. M. Rennie Tommi S. Jaakkola Computer Science and Artificial Intelligence Lab Massachusetts Institute of Technology Cambridge, MA, USA jrennie,tommi@csai... | 2004 | 178 |
2,594 | Real-Time Pitch Determination of One or More Voices by Nonnegative Matrix Factorization Fei Sha and Lawrence K. Saul Dept. of Computer and Information Science University of Pennsylvania, Philadelphia, PA 19104 {feisha,lsaul}@cis.upenn.edu Abstract An auditory “scene”, composed of overlapping acoustic sour... | 2004 | 179 |
2,595 | Hierarchical Distributed Representations for Statistical Language Modeling John Blitzer, Kilian Q. Weinberger, Lawrence K. Saul, and Fernando C. N. Pereira Department of Computer and Information Science, University of Pennsylvania Levine Hall, 3330 Walnut Street, Philadelphia, PA 19104 {blitzer,kilianw,lsaul,... | 2004 | 18 |
2,596 | Efficient Out-of-Sample Extension of Dominant-Set Clusters Massimiliano Pavan and Marcello Pelillo Dipartimento di Informatica, Universit`a Ca’ Foscari di Venezia Via Torino 155, 30172 Venezia Mestre, Italy {pavan,pelillo}@dsi.unive.it Abstract Dominant sets are a new graph-theoretic concept that has prove... | 2004 | 180 |
2,597 | Instance-Specific Bayesian Model Averaging for Classification Shyam Visweswaran Gregory F. Cooper Center for Biomedical Informatics Center for Biomedical Informatics Intelligent Systems Program Intelligent Systems Program Pittsburgh, PA 15213 Pittsburgh, PA 15213 sh... | 2004 | 181 |
2,598 | Hierarchical Eigensolver for Transition Matrices in Spectral Methods Chakra Chennubhotla∗and Allan D. Jepson† ∗Department of Computational Biology, University of Pittsburgh †Department of Computer Science, University of Toronto Abstract We show how to build hierarchical, reduced-rank representation for larg... | 2004 | 182 |
2,599 | Exponentiated Gradient Algorithms for Large-margin Structured Classification Peter L. Bartlett U.C.Berkeley bartlett@stat.berkeley.edu Michael Collins MIT CSAIL mcollins@csail.mit.edu Ben Taskar Stanford University btaskar@cs.stanford.edu David McAllester TTI at Chicago mcallester@tti-c.org A... | 2004 | 183 |
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