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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1,500 | Tight Bounds for the VC-Dimension of Piecewise Polynomial Networks Akito Sakurai School of Knowledge Science Japan Advanced Institute of Science and Technology Nomi-gun, Ishikawa 923-1211, Japan. CREST, Japan Science and Technology Corporation. ASakurai@jaist.ac.jp Abstract O(ws(s log d+log(d... | 1998 | 143 |
1,501 | The effect of eligibility traces on finding optimal memoryless policies in partially observable Markov decision processes John Loch Department of Computer Science University of Colorado Boulder, CO 80309-0430 loch@cs.colorado.edu Abstract Agents acting in the real world are confronted with the p... | 1998 | 144 |
1,502 | Exploratory Data Analysis Using Radial Basis Function Latent Variable Models Alan D. Marrs and Andrew R. Webb DERA St Andrews Road, Malvern Worcestershire U.K. WR14 3PS {marrs,webb}@signal.dera.gov.uk @British Crown Copyright 1998 Abstract Two developments of nonlinear latent variable models ... | 1998 | 145 |
1,503 | A VI model of pop out and asymmetry visual search Zhaoping Li University College London, z.li@ucl.ac.uk Abstract Visual search is the task of finding a target in an image against a background of distractors. Unique features of targets enable them to pop out against the background, while targets def... | 1998 | 146 |
1,504 | A High Performance k-NN Classifier Using a Binary Correlation Matrix Memory Ping Zhou zhoup@cs.york.ac.uk Jim Austin austin@cs.york.ac.uk John Kennedy johnk@cs.york.ac.uk Advanced Computer Architecture Group Department of Computer Science University of York, York YOW 500, UK Abstract ... | 1998 | 147 |
1,505 | Exploring Unknown Environments with Real-Time Search or Reinforcement Learning Sven Koenig College of Computing, Georgia Institute of Technology skoenig@cc.gatech.edu Abstract Learning Real-Time A* (LRTA*) is a popular control method that interleaves planning and plan execution and has been shown to s... | 1998 | 148 |
1,506 | Inference in Multilayer Networks Large Deviation Bounds Michael Kearns and Lawrence Saul AT&T Labs Research Shannon Laboratory 180 Park A venue A-235 Florham Park, NJ 07932 {mkearns ,lsaul}Oresearch.att. com Abstract • VIa We study probabilistic inference in large, layered Bayesian netw... | 1998 | 149 |
1,507 | Fisher Scoring and a Mixture of Modes Approach for Approximate Inference and Learning in Nonlinear State Space Models Thomas Briegel and Volker Tresp Siemens AG, Corporate Technology Dept. Information and Communications Otto-Hahn-Ring 6,81730 Munich, Germany {Thomas.Briegel, Volker.Tresp} @mchp.sie... | 1998 | 15 |
1,508 | Basis Selection For Wavelet Regression Kevin R. Wheeler Caelum Research Corporation NASA Ames Research Center Mail Stop 269-1 Moffett Field, CA 94035 kwheeler@mail.arc.nasa.gov Abstract Atam P. Dhawan College of Engineering University of Toledo 2801 W. Bancroft Street Toledo, OH 4360... | 1998 | 150 |
1,509 | Where does the population vector of motor cortical cells point during reaching movements? Pierre Baraduc* pbaraduc@snv.jussieu.fr Emmanuel Guigon guigon@ccr.jussieu.fr Yves Burnod ybteam@ccr.jussieu.fr INSERM U483, Universite Pierre et Marie Curie 9 quai St Bernard, 75252 Paris cedex 05, Fran... | 1998 | 151 |
1,510 | Probabilistic Modeling for Face Orientation Discrimination: Learning from Labeled and Unlabeled Data Shumeet Baluja baluja@cs.cmu.edu Justsystem Pittsburgh Research Center & School of Computer Science, Carnegie Mellon University Abstract This paper presents probabilistic modeling methods to solv... | 1998 | 16 |
1,511 | Direct Optimization of Margins Improves Generalization in Combined Classifiers Llew Mason,Peter Bartlett, Jonathan Baxter Department of Systems Engineering Australian National University, Canberra, ACT 0200, Australia {lmason, bartlett, jon }@syseng.anu.edu.au Abstract Cumulative training margin di... | 1998 | 17 |
1,512 | A N euromorphic Monaural Sound Localizer John G. Harris, Chiang-Jung Pu, and Jose C. Principe Department of Electrical & Computer Engineering University of Florida Gainesville, FL 32611 Abstract We describe the first single microphone sound localization system and its inspiration from theories o... | 1998 | 18 |
1,513 | Boxlets: a Fast Convolution Algorithm for Signal Processing and Neural Networks Patrice Y. Simard·, Leon Botton, Patrick Haffner and Yann LeCnn AT&T Labs-Research 100 Schultz Drive, Red Bank, NJ 07701-7033 patrice@microsoft.com {leon b ,haffner ,yann }@research.att.com Abstract Signal processing... | 1998 | 19 |
1,514 | A Randomized Algorithm for Pairwise Clustering Yoram Gdalyahu, Daphna Weinshall, Michael Werman Institute of Computer Science, The Hebrew University, 91904 Jerusalem, Israel {yoram,daphna,werman}@cs.huji.ac.il Abstract We present a stochastic clustering algorithm based on pairwise similarity of datapoint... | 1998 | 2 |
1,515 | Experimental Results on Learning Stochastic Memoryless Policies for Partially Observable Markov Decision Processes John K. Williams Department of Mathematics University of Colorado Boulder, CO 80309-0395 jkwillia@euclid.colorado.edu Abstract Satinder Singh AT &T Labs-Research 180 Park A... | 1998 | 20 |
1,516 | Attentional Modulation of Human Pattern Discrimination Psychophysics Reproduced by a Quantitative Model Laurent Itti, Jochen Braun, Dale K. Lee and Christof Koch {itti, achim, jjwen, koch}Oklab.caltech.edu Computation & Neural Systems, MSC 139-74 California Institute of Technology, Pasadena, CA 91125,... | 1998 | 21 |
1,517 | Signal Detection in Noisy Weakly-Active Dendrites Amit Manwani and Christof Koch {quixote,koch}@klab.caltech.edu Computation and Neural Systems Program California Institute of Technology Pasadena, CA 91125 Abstract Here we derive measures quantifying the information loss of a synaptic signal ... | 1998 | 22 |
1,518 | Kernel peA and De-Noising in Feature Spaces Sebastian Mika, Bernhard Scholkopf, Alex Smola Klaus-Robert Muller, Matthias Scholz, Gunnar Riitsch GMD FIRST, Rudower Chaussee 5, 12489 Berlin, Germany {mika, bs, smola, klaus, scholz, raetsch} @first.gmd.de Abstract Kernel PCA as a nonlinear feature extrac... | 1998 | 23 |
1,519 | Multiple Paired Forward-Inverse Models for Human Motor Learning and Control Masahiko Haruno* mharuno@hip.atr.co.jp Daniel M. Wolpert t wolpert@hera.ucl.ac.uk Mitsuo Kawato* o kawato(Q)hip.atr.co.jp * ATR Human Information Processing Research Laboratories 2-2 Hikaridai, Seika-cho, Soraku-gun, ... | 1998 | 24 |
1,520 | SMEM Algorithm for Mixture Models N aonori U eda Ryohei Nakano {ueda, nakano }@cslab.kecl.ntt.co.jp NTT Communication Science Laboratories Hikaridai, Seika-cho, Soraku-gun, Kyoto 619-0237 Japan Zoubin Ghahramani Geoffrey E. Hinton zoubin@gatsby.uc1.ac.uk g.hinton@ucl.ac.uk Gatsby Computationa... | 1998 | 25 |
1,521 | Learning Lie Groups for Invariant Visual Perception* Rajesb P. N. Rao and Daniel L. Ruderman Sloan Center for Theoretical Neurobiology The Salk Institute La Jolla, CA 92037 {rao,ruderrnan}@salk.edu Abstract One of the most important problems in visual perception is that of visual invariance: how ar... | 1998 | 26 |
1,522 | Tractable Variational Structures for Approximating Graphical Models David Barber Wim Wiegerinck {davidb,wimw}@mbfys,kun,nl RWCP* Theoretical Foundation SNNt University of Nijmegen 6525 EZ Nijmegen, The Netherlands. Abstract Graphical models provide a broad probabilistic framework with applicatio... | 1998 | 27 |
1,523 | A Micropower CMOS Adaptive Amplitude and Shift Invariant Vector Quantiser Richard J. Coggins, Raymond J.W. Wang and Marwan A. Jabri Computer Engineering Laboratory School of Electrical and Infonnation Engineering, J03 University of Sydney, 2006, Australia. {richardc, jwwang, marwan} @seda1.usyd.edu.au... | 1998 | 28 |
1,524 | Convergence Rates of Algorithms for Visual Search: Detecting Visual Contours A.L. Yuille Smith-Kettlewell Inst. San Francisco, CA 94115 Abstract James M. Coughlan Smith-Kettlewell Inst. San Francisco, CA 94115 This paper formulates the problem of visual search as Bayesian inference and def... | 1998 | 29 |
1,525 | Learning a Continuous Hidden Variable Model for Binary Data Daniel D. Lee Bell Laboratories Lucent Technologies Murray Hill, NJ 07974 ddlee~bell-labs.com Haim Sompolinsky Racah Institute of Physics and Center for Neural Computation Hebrew University Jerusalem, 91904, Israel haim~fiz.... | 1998 | 3 |
1,526 | Learning to Find Pictures of People Sergey Ioffe Computer Science Division U.C. Berkeley Berkeley CA 94720 iojJe(Cj)cs. be1·keley. edu David Forsyth Computer Sciencp Division U.C. Berkeley Berkeley CA 94720 daf@cs.beTkeley. edv Abstract Finding articulated objects, like people, in pi... | 1998 | 30 |
1,527 | Visualizing Group Structure* Marcus Held, Jan Puzicha, and Joachim M. Buhmann Institut fur Informatik III, RomerstraBe 164, D-53117 Bonn, Germany email: {heldjanjb}.cs.uni-bonn.de. VVVVVV: http://vvv-dbv.cs.uni-bonn.de Abstract Cluster analysis is a fundamental principle in exploratory data anal... | 1998 | 31 |
1,528 | Modeling Surround Suppression in VI Neurons with a Statistically-Derived Normalization Model Eero P. Simoncelli Center for Neural Science, and Courant Institute of Mathematical Sciences New York University eero.simoncelli@nyu.edu Abstract Odelia Schwartz Center for Neural Science New York ... | 1998 | 32 |
1,529 | Familiarity Discrimination of Radar Pulses Eric Grangerl, Stephen Grossberg2 Mark A. RUbin2 , William W. Streilein2 1 Department of Electrical and Computer Engineering Ecole Poly technique de Montreal Montreal, Qc. H3C 3A 7 CAN ADA 2Department of Cognitive and Neural Systems, Boston University B... | 1998 | 33 |
1,530 | Graphical Models for Recognizing Human Interactions Nuria M. Oliver, Barbara Rosario and Alex Pentland 20 Ames Street, E15-384C, Media Arts and Sciences Laboratory, MIT Cambridge, MA 02139 {nuria, rosario, sandy}@media.mit.edu Abstract We describe a real-time computer vision and machine learning... | 1998 | 34 |
1,531 | An entropic estimator for structure discovery Matthew Brand Mitsubishi Electric Research Laboratories, 201 Broadway, Cambridge MA 02139 brand@merl.com Abstract We introduce a novel framework for simultaneous structure and parameter learning in hidden-variable conditional probability models, based on a... | 1998 | 35 |
1,532 | The Effect of Correlations on the Fisher Information of Population Codes Hyoungsoo Yoon hyoung@fiz.huji.ac.il Haim Sompolinsky hairn@fiz.huji.ac.il Racah Institute of Physics and Center for Neural Computation Hebrew University, Jerusalem 91904, Israel Abstract We study the effect of correlate... | 1998 | 36 |
1,533 | Spike-Based Compared to Rate-Based Hebbian Learning Richard Kempter* Institut fur Theoretische Physik Technische Universitat Munchen D-85747 Garching, Germany Wulfram Gerstner Swiss Federal Institute of Technology Center of Neuromimetic Systems, EPFL-DI CH-1015 Lausanne, Switzerland J. Leo... | 1998 | 37 |
1,534 | Contrast adaptation in simple cells by changing the transmitter release probability Peter Adorjan Klaus Obennayer Dept. of Computer Science, FR2-1, Technical University Berlin Franklinstrasse 28/2910587 Berlin, Germany {adp, oby} @cs.tu-berlin.de http://www.ni.cs.tu-berlin.de Abstract The con... | 1998 | 38 |
1,535 | Optimizing Correlation Algorithms for Hardware-based Transient Classification R. Timothy Edwardsl, Gert Cauwenberghsl, and Fernando J. Pineda2 1 Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD 21218 2 Applied Physics Laboratory, Johns Hopkins University, Laurel, MD 20723 e-ma... | 1998 | 39 |
1,536 | Convergence of The Wake-Sleep Algorithm Shiro Ikeda PRESTO,JST Wako, Saitama, 351-0198, Japan shiro@brain.riken.go.jp Shun-ichi Amari RIKEN Brain Science Institute Wako, Saitama, 351-0198,Japan amari@brain.riken.go.jp Hiroyuki Nakahara RIKEN Brain Science Institute hiro@brain.riken.go.j... | 1998 | 4 |
1,537 | Information Maximization in Single Neurons Martin Stemmler and Christof Koch Computation and Neural Systems Program Caltech 139-74 Pasadena, CA 91 125 Email: stemmler@klab.caltech.edu.koch@klab.caltech.edu Abstract Information from the senses must be compressed into the limited range of firing r... | 1998 | 40 |
1,538 | Mechanisms of generalization perceptual learning • In Zili Lin Rutgers University, Newark Daphna Weinshall Hebrew University, Israel Abstract The learning of many visual perceptual tasks has been shown to be specific to practiced stimuli, while new stimuli require re-Iearning from scratch.... | 1998 | 41 |
1,539 | Probabilistic Image Sensor Fusion Ravi K. Sharma1 , Todd K. Leen2 and Misha Pavel1 1 Department of Electrical and Computer Engineering 2Department of Computer Science and Engineering Oregon Graduate Institute of Science and Technology P.O. Box 91000, Portland, OR 97291-1000 Email: {ravi,pavel}@ece.ogi... | 1998 | 42 |
1,540 | Tight Bounds for the VC-Dimension of Piecewise Polynomial Networks Akito Sakurai School of Knowledge Science Japan Advanced Institute of Science and Technology Nomi-gun, Ishikawa 923-1211, Japan. CREST, Japan Science and Technology Corporation. ASakurai@jaist.ac.jp Abstract O(ws(s log d+log(d... | 1998 | 43 |
1,541 | Phase Diagram and Storage Capacity of Sequence Storing Neural Networks A. During Dept. of Physics Oxford University Oxford OX 1 3NP United Kingdom a.duringl @physics.oxford.ac.uk D. Sherrington Dept. of Physics Oxford University Oxford OX I 3NP United Kingdom A. C. C. Coolen De... | 1998 | 44 |
1,542 | Example Based Image Synthesis of Articulated Figures Trevor Darrell Interval Research. 1801C Page Mill Road. Palo Alto CA 94304 trevor@interval.com, http://www.interval.com/-trevor/ Abstract We present a method for learning complex appearance mappings. such as occur with images of articulated objec... | 1998 | 45 |
1,543 | Shrinking the Thbe: A New Support Vector Regression Algorithm Bernhard SchOikopr§,*, Peter Bartlett*, Alex Smola§,r, Robert Williamson* § GMD FIRST, Rudower Chaussee 5, 12489 Berlin, Germany * FEITIRSISE, Australian National University, Canberra 0200, Australia bs, smola@first.gmd.de, Peter.Bartlett, Bob... | 1998 | 46 |
1,544 | Lazy Learning Meets the Recursive Least Squares Algorithm Mauro Birattari, Gianluca Bontempi, and Hugues Bersini Iridia - Universite Libre de Bruxelles Bruxelles, Belgium {mbiro, gbonte, bersini} @ulb.ac.be Abstract Lazy learning is a memory-based technique that, once a query is received, extracts ... | 1998 | 47 |
1,545 | Reinforcement Learning for Trading John Moody and Matthew Saffell* Oregon Graduate Institute, CSE Dept. P.O. Box 91000, Portland, OR 97291-1000 {moody, saffell }@cse.ogi.edu Abstract We propose to train trading systems by optimizing financial objective functions via reinforcement learning. The perform... | 1998 | 48 |
1,546 | Distributional Population Codes and Multiple Motion Models Richard S. Zemel University of Arizona zemel@u.arizona.edu Peter Dayan Gatsby Computational Neuroscience Unit dayan@gatsby.ucl.ac.uk Abstract Most theoretical and empirical studies of population codes make the assumption that under... | 1998 | 49 |
1,547 | Mean field methods for classification with Gaussian processes Manfred Opper Neural Computing Research Group Division of Electronic Engineering and Computer Science Aston University Birmingham B4 7ET, UK. opperm~aston.ac.uk Ole Winther Theoretical Physics II, Lund University, S6lvegatan 14 A S... | 1998 | 5 |
1,548 | USING COLLECTIVE INTELLIGENCE TO ROUTE INTERNET TRAFFIC David H. Wolpert NASA Ames Research Center Moffett Field, CA 94035 dhw@ptolemy.arc.nasa.gov Kagan Turner NASA Ames Research Center Moffett Field, CA 94035 kagan@ptolemy.arc.nasa.gov Jeremy Frank NASA Ames Research Center Moffett... | 1998 | 50 |
1,549 | Sparse Code Shrinkage: Denoising by Nonlinear Maximum Likelihood Estimation Aapo Hyvarinen, Patrik Hoyer and Erkki Oja Helsinki University of Technology Laboratory of Computer and Information Science P.O. Box 5400, FIN-02015 HUT, Finland aapo.hyvarinen@hut.fi,patrik.hoyer@hut.fi,erkki.oja@hut.fi ht... | 1998 | 51 |
1,550 | Finite-dimensional approximation of Gaussian processes Giancarlo Ferrari Trecate Dipartimento di Informatica e Sistemistica, Universita di Pavia, Via Ferrata 1, 27100 Pavia, Italy ferrari@conpro.unipv.it Christopher K. I. Williams Department of Artificial Intelligence, University of Edinburgh, 5... | 1998 | 52 |
1,551 | Controlling the Complexity of HMM Systems by Regularization Christoph Neukirchen, Gerhard Rigoll Department of Computer Science Gerhard-Mercator-University Duisburg 47057 Duisburg, Germany email: {chn.rigoll}@fb9-ti.uni-duisburg.de Abstract This paper introduces a method for regularization ofHMM... | 1998 | 53 |
1,552 | Computation of Smooth Optical Flow in a Feedback Connected Analog Network Alan Stocker * Institute of Neuroinforrnatics University and ETH Zi.irich Winterthurerstrasse 190 8057 Zi.irich, Switzerland Abstract Rodney Douglas Institute of Neuroinforrnatics University and ETH Zi.irich Winte... | 1998 | 54 |
1,553 | Learning to estimate scenes from images William T. Freeman and Egon C. Pasztor MERL, Mitsubishi Electric Research Laboratory 201 Broadway; Cambridge, MA 02139 freeman@merl.com, pasztor@merl.com Abstract We seek the scene interpretation that best explains image data. For example, we may want to infe... | 1998 | 55 |
1,554 | Learning curves for Gaussian processes Peter Sollich * Department of Physics, University of Edinburgh Edinburgh EH9 3JZ, U.K. Email: P.Sollich<Oed.ac . uk Abstract I consider the problem of calculating learning curves (i.e., average generalization performance) of Gaussian processes used for regression... | 1998 | 56 |
1,555 | Facial Memory is Kernel Density Estimation (Almost) Matthew N. Dailey Garrison W. Cottrell Department of Computer Science and Engineering U.C. San Diego La Jolla, CA 92093-0114 {mdailey,gary}@cs.ucsd.edu Abstract Thomas A. Busey Department of Psychology Indiana University Bloomington... | 1998 | 57 |
1,556 | VLSI Implementation of Motion Centroid Localization for Autonomous Navigation Ralph Etienne-Cummings Dept. of ECE, Johns Hopkins University, Baltimore, MD Viktor Gruev Dept. of ECE, Johns Hopkins University, Baltimore, MD Abstract Mohammed Abdel Ghani Dept. ofEE, S. Illinois Unive... | 1998 | 58 |
1,557 | Discontinuous Recall Transitions Induced By Competition Between Short- and Long-Range Interactions in Recurrent Networks N.S. Skantzos, C.F. Beckmann and A.C.C. Coolen Dept of Mathematics, King's College London, Strand, London WC2R 2LS, UK E-mail: skantzos@mth.kcl.ac.uktcoolen@mth.kcl.ac.uk Abstract ... | 1998 | 59 |
1,558 | Learning from Dyadic Data Thomas Hofmann·, Jan Puzicha+, Michael I. Jordan· • Center for Biological and Computational Learning, M .I.T Cambridge, MA, {hofmann, jordan}@ai.mit.edu + Institut fi.ir Informatik III , Universitat Bonn, Germany, jan@cs.uni-bonn.de Abstract Dyadzc data refers to a domain wit... | 1998 | 6 |
1,559 | An Integrated Vision Sensor for the Computation of Optical Flow Singular Points Charles M. Higgins and Christof Koch Division of Biology, 139-74 California Institute of Technology Pasadena, CA 91125 [chuck,koch]@klab.caltech.edu Abstract A robust, integrative algorithm is presented for computing... | 1998 | 60 |
1,560 | Robust. Efficient, Globally-Optimized Reinforcement Learning with the Parti-Game Algorithm Mohammad A. AI-Ansari and Ronald J. Williams College of Computer Science, 161 CN Northeastern University Boston, MA 02115 alansar@ccs.neu.edu, rjw@ccs.neu.edu Abstract Parti-game (Moore 1994a; Moore 199... | 1998 | 61 |
1,561 | Learning a Hierarchical Belief Network of Independent Factor Analyzers H. Attias* hagai@gatsby.ucl.ac.uk Sloan Center for Theoretical Neurobiology, Box 0444 University of California at San Francisco San Francisco, CA 94143-0444 Abstract Many belief networks have been proposed that are composed o... | 1998 | 62 |
1,562 | A Reinforcement Learning Algorithm in Partially Observable Environments Using Short-Term Memory Nobuo Suematsu and Akira Hayashi Faculty of Computer Sciences Hiroshima City University 3-4-1 Ozuka-higashi, Asaminami-ku, Hiroshima 731-3194 Japan { suematsu,akira} @im.hiroshima-cu.ac.jp Abstract ... | 1998 | 63 |
1,563 | Maximum-Likelihood Continuity Mapping (MALCOM): An Alternative to HMMs David A. Nix dnix@lanl.gov Computer Research & Applications CIC-3, MS B265 Los Alamos National Laboratory Los Alamos, NM 87545 John E. Hogden hogden@lanl.gov Computer Research & Applications CIC-3, MS B265 Los Ala... | 1998 | 64 |
1,564 | Semiparametric Support Vector and Linear Programming Machines Alex J. Smola, Thilo T. Frie6, and Bernhard Scholkopf GMD FIRST, Rudower Chaussee 5, 12489 Berlin {smola, friess, bs }@first.gmd.de Abstract Semiparametric models are useful tools in the case where domain knowledge exists about the funct... | 1998 | 65 |
1,565 | Regularizing AdaBoost Gunnar Riitsch, Takashi Onoda; Klaus R. M iiller GMD FIRST, Rudower Chaussee 5, 12489 Berlin, Germany {raetsch, onoda, klaus }@first.gmd.de Abstract Boosting methods maximize a hard classification margin and are known as powerful techniques that do not exhibit overfitting for low... | 1998 | 66 |
1,566 | The Bias-Variance Tradeoff and the Randomized GACV Grace Wahba, Xiwu Lin and Fangyu Gao Dept of Statistics Univ of Wisconsin 1210 W Dayton Street Madison, WI 53706 wahba,xiwu,fgao@stat.wisc.edu Dong Xiang SAS Institute, Inc. SAS Campus Drive Cary, NC 27513 sasdxx@unx.sas.com Ronal... | 1998 | 67 |
1,567 | DTs: Dynamic Trees Christopher K. I. Williams Nicholas J. Adams Institute for Adaptive and Neural Computation Division of Informatics, 5 Forrest Hill Edinburgh, EHI 2QL, UK. http://www.anc.ed.ac . uk/ ckiw~dai.ed.ac.uk nicka~dai.ed.ac.uk Abstract In this paper we introduce a new class of i... | 1998 | 68 |
1,568 | Adding Constrained Discontinuities to Gaussian Process Models of Wind Fields Dan Cornford* Ian T. Nabney Christopher K. I. Williamst Neural Computing Research Group Aston University, BIRMINGHAM, B4 7ET, UK d.comford@aston.ac.uk Abstract Gaussian Processes provide good prior models for spatial... | 1998 | 69 |
1,569 | Call-based Fraud Detection in Mobile Communication Networks using a Hierarchical Regime-Switching Model Jaakko Hollmen Helsinki University of Technology Lab. of Computer and Information Science P.O. Box 5400, 02015 HUT, Finland laakko.Hollmen@hut.fi Volker Tresp Siemens AG, Corporate Technolo... | 1998 | 7 |
1,570 | The Belief in TAP Yoshiyuki Kabashima Dept. of Compt. IntI. & Syst. Sci. Tokyo Institute of Technology Yokohama 226, Japan David Saad Neural Computing Research Group Aston University Birmingham B4 7ET, UK Abstract We show the similarity between belief propagation and TAP, for decoding c... | 1998 | 70 |
1,571 | Synergy and redundancy among brain cells of behaving monkeys Itay Gat· Institute of Computer Science and Center for Neural Computation The Hebrew University, Jerusalem 91904, Israel Abstract Naftali Tishby t NEC Research Institute 4 Independence Way Princeton N J 08540 Determining the r... | 1998 | 71 |
1,572 | Classification on Pairwise Proximity Data Thore Graepelt , Ralf Herbrichi , Peter Bollmann-Sdorrat , Klaus Obermayert Technical University of Berlin, t Statistics Research Group, Sekr. FR 6-9, t Neural Information Processing Group, Sekr. FR 2-1 , Franklinstr. 28/29, 10587 Berlin, Germany Abstract ... | 1998 | 72 |
1,573 | Using Analytic QP and Sparseness to Speed Training of Support Vector Machines John C. Platt Microsoft Research 1 Microsoft Way Redmond, WA 98052 jplatt@microsoft.com Abstract Training a Support Vector Machine (SVM) requires the solution of a very large quadratic programming (QP) problem. This... | 1998 | 73 |
1,574 | Dynamically Adapting Kernels in Support Vector Machines N ello Cristianini Colin Campbell Dept. of Engineering Mathematics University of Bristol, UK nello.cristianini@bristol.ac.uk Dept. of Engineering Mathematics University of Bristol, UK c.campbell@bristol.ac.uk John Shawe-Taylor Dept... | 1998 | 74 |
1,575 | Temporally Asymmetric Hebbian Learning, Spike Timing and Neuronal Response Variability L.F. Abbott and Sen Song Volen Center and Department of Biology Brandeis University Waltham MA 02454 Abstract Recent experimental data indicate that the strengthening or weakening of synaptic connections betwe... | 1998 | 75 |
1,576 | Learning Mixture Hierarchies N uno Vasconcelos Andrew Lippman MIT Media Laboratory, 20 Ames St, EI5-320M, Cambridge, MA 02139, {nuno,lip} @media.mit.edu, http://www.media.mit.edwnuno Abstract The hierarchical representation of data has various applications in domains such as data mining, machine vi... | 1998 | 76 |
1,577 | On the optimality of incremental neural network algorithms Ron Meir* Department of Electrical Engineering Technion, Haifa 32000, Israel rmeir@dumbo.technion.ac.il Vitaly Maiorovt Department of Mathematics Technion, Haifa 32000, Israel maiorov@tx.technion.ac.il Abstract We study the appr... | 1998 | 77 |
1,578 | Optimizing admission control while ensuring quality of service in multimedia networks via reinforcement learning* Timothy X Brown t , Hui Tong t , Satinder Singh+ t Electrical and Computer Engineering + Computer Science University of Colorado Boulder, CO 80309-0425 {timxb, tongh, baveja}@colorad... | 1998 | 78 |
1,579 | Coding time-varying signals using sparse, shift-invariant representations Michael S. Lewicki* lewickiCsalk.edu Terrence J. Sejnowski terryCsalk.edu Howard Hughes Medical Institute Computational Neurobiology Laboratory The Salk Institute 10010 N. Torrey Pines Rd. La Jolla, CA 92037 Abstr... | 1998 | 79 |
1,580 | Analyzing and Visualizing Single-Trial Event-Related Potentials Tzyy-Ping Jung1,2, Scott Makeig2,3, Marissa Westerfield2 Jeanne Townsend2, Eric Courchesne2, Terrence J. Sejnowskp,2 1 Howard Hughes Medical Institute and Computational Neurobiology Laboratory The Salk Institute, P.O. Box 85800, San Diego, C... | 1998 | 8 |
1,581 | Evidence for a Forward Dynamics Model in Human Adaptive Motor Control Nikhil Bhushan and Reza Shadmehr Dept. of Biomedical Engineering Johns Hopkins University, Baltimore, MD 21205 Email: nbhushan@bme.jhu.edu, reza@bme.jhu.edu Abstract Based on computational principles, the concept of an internal ... | 1998 | 80 |
1,582 | Restructuring Sparse High Dimensional Data for Effective Retrieval Charles Lee Isbell, Jr. AT&T Labs 180 Park Avenue Room A255 Florham Park, NJ 07932-0971 Paul Viola Artificial Intelligence Laboratory Massachusetts Institute of Technology Cambridge, MA 02139 Abstract The task in text re... | 1998 | 81 |
1,583 | Classification in Non-Metric Spaces Daphna Weinshalll ,2 David W. Jacobs l Yoram Gdalyahu2 1 NEC Research Institute, 4 Independence Way, Princeton, NJ 08540, USA 2Inst. of Computer Science, Hebrew University of Jerusalem, Jerusalem 91904, Israel Abstract A key question in vision is how to represent... | 1998 | 82 |
1,584 | Approximate Learning of Dynamic Models Xavier Boyen Computer Science Dept. 1 A Stanford, CA 94305-9010 xb@cs.stanford.edu Abstract Daphne Koller Computer Science Dept. 1 A Stanford, CA 94305-9010 koller@cs.stanford.edu Inference is a key component in learning probabilistic models from part... | 1998 | 83 |
1,585 | Independent Component Analysis of Intracellular Calcium Spike Data Klaus Prank, Julia Borger, Alexander von zur Miihlen, Georg Brabant, Christof Schoil Department of Clinical Endocrinology Medical School Hannover D-30625 Hannover Germany Abstract Calcium (Ca2+)is an ubiquitous intracellular m... | 1998 | 84 |
1,586 | A Model for Associative Multiplication G. Bjorn Christianson* Department of Psychology McMaster University Hamilton,Ont. L8S 4Kl bjorn@caltech.edu Suzanna Becker Department of Psychology McMaster University Hamilton, Onto L8S 4Kl becker@mcmaster.ca Abstract Despite the fact that ment... | 1998 | 85 |
1,587 | Batch and On-line Parameter Estimation of Gaussian Mixtures Based on the Joint Entropy Yoram Singer AT&T Labs singer@research.att.com Manfred K. Warmuth University of California, Santa Cruz manfred@cse.ucsc.edu Abstract We describe a new iterative method for parameter estimation of Gaussian m... | 1998 | 86 |
1,588 | Learning Macro-Actions in Reinforcement Learning Jette Randlttv Niels Bohr Inst., Blegdamsvej 17, University of Copenhagen, DK-21 00 Copenhagen 0, Denmark randlov@nbi.dk Abstract We present a method for automatically constructing macro-actions from scratch from primitive actions during the re... | 1998 | 87 |
1,589 | Fast Neural Network Emulation of Dynamical Systems for Computer Animation Radek Grzeszczuk 1 Demetri Terzopoulos 2 Geoffrey Hinton 2 1 Intel Corporation Microcomputer Research Lab 2200 Mission College Blvd. Santa Clara, CA 95052, USA 2 University of Toronto Department of Computer Science ... | 1998 | 88 |
1,590 | Neural Networks for Density Estimation Malik Magdon-Ismail* magdon~cco.caltech.edu Caltech Learning Systems Group Department of Electrical Engineering California Institute of Technology 136-93 Pasadena, CA, 91125 Amir Atiya amir~deep.caltech.edu Caltech Learning Systems Group Department of... | 1998 | 89 |
1,591 | Learning Nonlinear Dynamical Systems using an EM Algorithm Zoubin Ghahramani and Sam T. Roweis Gatsby Computational Neuroscience Unit University College London London WC1N 3AR, U.K. http://www.gatsby.ucl.ac.uk/ Abstract The Expectation-Maximization (EM) algorithm is an iterative procedure for ma... | 1998 | 9 |
1,592 | Improved Switching among Temporally Abstract Actions Richard S. Sutton Satinder Singh AT&T Labs Florham Park, NJ 07932 { sutton,baveja}@research.att.com Doina Precup Balaraman Ravindran University of Massachusetts Amherst, MA 01003-4610 { dprecup,ravi}@cs.umass.edu Abstract In robotics ... | 1998 | 90 |
1,593 | Dynamics of Supervised Learning with Restricted Training Sets A.C.C. Coolen Dept of Mathematics King's College London Strand, London WC2R 2LS, UK tcoolen @mth.kcl.ac.uk D. Saad Neural Computing Research Group Aston University Birmingham B4 7ET, UK saadd@aston.ac.uk Abstract We stu... | 1998 | 91 |
1,594 |
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'(" )*,+.-0/132547698 :<; =>@? * 8BA 1 + CDFE G D3HIJLK MON D3GQPSRUTUV WYX<Z X\[<]^E P _.`Ba0bYc<d eSf0gihk... | 1998 | 92 |
1,595 | A Polygonal Line Algorithm for Constructing Principal Curves Balazs Kegl, Adam Krzyzak Dept. of Computer Science Concordia University 1450 de Maisonneuve Blvd. W. Montreal, Canada H3G IM8 kegl@cs.concordia.ca krzyzak@cs.concordia.ca Tamas Linder Dept. of Mathematics and Statistics Qu... | 1998 | 93 |
1,596 | Neuronal Regulation Implements Efficient Synaptic Pruning Gal Chechik and Isaac Meilijson School of Mathematical Sciences Tel Aviv University, Tel Aviv 69978, Israel ggal@math.tau.ac.il isaco@math.tau.ac.il Eytan Ruppin Schools of Medicine and Mathematical Sciences Tel Aviv University, Tel Av... | 1998 | 94 |
1,597 | Finite-Sample Convergence Rates for Q-Learning and Indirect Algorithms Michael Kearns and Satinder Singh AT&T Labs 180 Park Avenue Florham Park, NJ 07932 {mkearns,baveja }@research.att.com Abstract In this paper, we address two issues of long-standing interest in the reinforcement learning liter... | 1998 | 95 |
1,598 | Global Optimisation of Neural Network Models Via Sequential Sampling J oao FG de Freitas Cambridge University Engineering Department Cambridge CB2 1PZ England jfgf@eng.cam.ac.uk [Corresponding author] Mahesan Niranjan Cambridge University Engineering Department Cambridge CB2 1PZ England... | 1998 | 96 |
1,599 | Non-linear PI Control Inspired by Biological Control Systems Lyndon J. Brown Gregory E. Gonye James S. Schwaber * Experimental Station, E.!. DuPont deNemours & Co. Wilmington, DE 19880 Abstract A non-linear modification to PI control is motivated by a model of a signal transduction pathway activ... | 1998 | 97 |
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