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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1,100 | Family Discovery Stephen M. Omohundro NEC Research Institute 4 Independence Way, Princeton, N J 08540 om@research.nj.nec.com Abstract "Family discovery" is the task of learning the dimension and structure of a parameterized family of stochastic models. It is especially appropriate when the training ex... | 1995 | 55 |
1,101 | Modeling Interactions of the Rat's Place and Head Direction Systems A. David Redish and David S. Touretzky Computer Science Department & Center for the Neural Basis of Cognition Carnegie Mellon University, Pittsburgh PA 15213-3891 Internet: {dredi sh, ds t}@es . emu. edu Abstract We have developed ... | 1995 | 56 |
1,102 | Empirical Entropy Manipulation for Real-World Problems Paul Viola: Nicol N. Schraudolph, Terrence J. Sejnowski Computational Neurobiology Laboratory The Salk Institute for Biological Studies 10010 North Torrey Pines Road La Jolla, CA 92037-1099 viola@salk.edu Abstract No finite sample is suff... | 1995 | 57 |
1,103 | A Neural Network Model of 3-D Lightness Perception Luiz Pessoa Federal Univ. of Rio de Janeiro Rio de Janeiro, RJ, Brazil pessoa@cos.ufrj.br Abstract William D. Ross Boston University Boston, MA 02215 bill@cns.bu.edu A neural network model of 3-D lightness perception is presented whi... | 1995 | 58 |
1,104 | Adaptive Retina with Center-Surround Receptive Field Shih-Chii Lin and Kwabena Boahen Computation and Neural Systems 139-74 California Institute of Technology Pasadena, CA 91125 shih@pcmp.caltech.edu, buster@pcmp.caltech.edu Abstract Both vertebrate and invertebrate retinas are highly efficient ... | 1995 | 59 |
1,105 | Laterally Interconnected Self-Organizing Maps in Hand-Written Digit Recognition Yoonsuck Choe, Joseph Sirosh, and Risto Miikkulainen Department of Computer Sciences The University of Texas at Austin Austin, TX 78712 yschoe,sirosh,risto@cs. u texas .ed u Abstract An application of laterally inter... | 1995 | 6 |
1,106 | Does the Wake-sleep Algorithm Produce Good Density Estimators? Peter Dayan Brendan J. Frey, Geoffrey E. Hinton Department of Computer Science University of Toronto Toronto, ON M5S 1A4, Canada {frey, hinton} @cs.toronto.edu Department of Brain and Cognitive Sciences Massachusetts Institute of ... | 1995 | 60 |
1,107 | EM Optimization of Latent-Variable Density Models Christopher M Bishop, Markus Svensen and Christopher K I Williams Neural Computing Research Group Aston University, Birmingham, B4 7ET, UK c.m.bishop~aston.ac.uk svensjfm~aston.ac.uk c.k.i.williams~aston.ac.uk Abstract There is currently considerabl... | 1995 | 61 |
1,108 | Modern Analytic Techniques to Solve the Dynamics of Recurrent Neural Networks A.C.C. Coolen Dept. of Mathematics King's College London Strand, London WC2R 2LS, U.K. S.N. Laughton Dept. of Physics - Theoretical Physics University of Oxford 1 Keble Road, Oxford OX1 3NP, U.K. D. Sherrington .... | 1995 | 62 |
1,109 | A Realizable Learning Task which Exhibits Overfitting Siegfried Bos Laboratory for Information Representation, RIKEN, Hirosawa 2-1, Wako-shi, Saitama, 351-01, Japan email: boes@zoo.riken.go.jp Abstract In this paper we examine a perceptron learning task. The task is realizable since it is provid... | 1995 | 63 |
1,110 | Simulation of a Thalamocortical Circuit for Computing Directional Heading in the Rat Hugh T. Blair* Department of Psychology Yale University New Haven, CT 06520-8205 tadb@minerva.cis.yale.edu Abstract Several regions of the rat brain contain neurons known as head-direction celis, which encode th... | 1995 | 64 |
1,111 | Clustering data through an analogy to the Potts model Marcelo Blatt, Shai Wiseman and Eytan Domany Department of Physics of Complex Systems, The Weizmann Institute of Science, Rehovot 76100, Israel Abstract A new approach for clustering is proposed. This method is based on an analogy to a physical ... | 1995 | 65 |
1,112 | Learning Fine Motion by Markov Mixtures of Experts Marina Meilii Dept. of Elec. Eng. and Computer Sci. Massachussetts Inst. of Technology Cambridge, MA 02139 mmp@ai.mit.edu Michael I. J Ol'dan Dept.of Brain and Cognitive Sciences Massachussetts Inst. of Technology Cambridge, MA 02139 jo... | 1995 | 66 |
1,113 | Stable Linear Approximations to Dynamic Programming for Stochastic Control Problems with Local Transitions Benjamin Van Roy and John N. Tsitsiklis Laboratory for Information and Decision Systems Massachusetts Institute of Technology Cambridge, MA 02139 e-mail: bvr@mit.edu, jnt@mit.edu Abstract ... | 1995 | 67 |
1,114 | Generalisation of A Class of Continuous Neural Networks John Shawe-Taylor Dept of Computer Science, Royal Holloway, University of London, Egham, Surrey TW20 OEX, UK Email: johnCdcs.rhbnc.ac . uk Jieyu Zhao* IDSIA, Corso Elvezia 36, 6900-Lugano, Switzerland Email: jieyuCcarota.idsia.ch A... | 1995 | 68 |
1,115 | Visual gesture-based robot guidance with a modular neural system E. Littmann, Abt. Neuroinformatik, Fak. f. Informatik Universitat Ulm, D-89069 Ulm, FRG enno@neuro.informatik.uni-ulm.de A. Drees, and H. Ritter AG Neuroinformatik, Techn. Fakultat Univ. Bielefeld, D-33615 Bielefeld, FRG andrea,... | 1995 | 69 |
1,116 | hnproved Silicon Cochlea • uSIng Compatible Lateral Bipolar Transistors Andre van Schalk, Eric Fragniere, Eric Vittoz MANTRA Center for Neuromimetic Systems Swiss Federal Institute of Technology CH-IOI5 Lausanne email: vschaik@di.epfl.ch Abstract Analog electronic cochlear models need expo... | 1995 | 7 |
1,117 | Symplectic Nonlinear Component Analysis Lucas C. Parra Siemens Corporate Research 755 College Road East, Princeton, NJ 08540 lucas@scr.siemens.com Abstract Statistically independent features can be extracted by finding a factorial representation of a signal distribution. Principal Component Anal... | 1995 | 70 |
1,118 | Independent Component Analysis of Electroencephalographic Data Scott Makeig Naval Health Research Center P.O. Box 85122 San Diego CA 92186-5122 scott~cplJmmag.nhrc.navy.mil Tzyy-Ping Jung Naval Health Research Center and Computational Neurobiology Lab The Salk Institute, P.O. Box 85800 ... | 1995 | 71 |
1,119 | Competence Acquisition in an Autonomous Mobile Robot using Hardware Neural Techniques. Geoff Jackson and Alan F. Murray Department of Electrical Engineering Edinburgh University Edinburgh, ER9 3JL Scotland, UK gbj@ee.ed.ac.uk,afm@ee.ed.ac.uk Abstract In this paper we examine the practical ... | 1995 | 72 |
1,120 | Gaussian Processes for Regression Christopher K. I. Williams Neural Computing Research Group Aston University Birmingham B4 7ET, UK c.k.i.williams~aston.ac.uk Carl Edward Rasmussen Department of Computer ,Science University of Toronto Toronto, ONT, M5S lA4, Canada carl~cs.toronto.edu Ab... | 1995 | 73 |
1,121 | Reorganisation of Somatosensory Cortex after Tactile Training Rasmus S. Petersen John G. Taylor Centre for Neural Networks, King's College London Strand, London WC2R 2LS, UK Abstract Topographic maps in primary areas of mammalian cerebral cortex reorganise as a result of behavioural training. The n... | 1995 | 74 |
1,122 | Prediction of Beta Sheets in Proteins Anders Krogh The Sanger Centre Hinxton, Carobs CBIO IRQ, UK. Email: krogh@sanger.ac. uk S~ren Kamaric Riis Electronics Institute, Building 349 Technical University of Denmark 2800 Lyngby, Denmark Email: riis@ei.dtu.dk Abstract Most current methods f... | 1995 | 75 |
1,123 | Active Learning in Multilayer Perceptrons Kenji Fukumizu Information and Communication R&D Center, Ricoh Co., Ltd. 3-2-3, Shin-yokohama, Yokohama, 222 Japan E-mail: fuku@ic.rdc.ricoh.co.jp Abstract We propose an active learning method with hidden-unit reduction. which is devised specially for mu... | 1995 | 76 |
1,124 | A model of transparent motion and non-transparent motion aftereffects Alexander Grunewald* Max-Planck Institut fur biologische Kybernetik Spemannstrafie 38 D-72076 Tubingen, Germany Abstract A model of human motion perception is presented. The model contains two stages of direction selective uni... | 1995 | 77 |
1,125 | Improved Gaussian Mixture Density Estimates Using Bayesian Penalty Terms and Network Averaging Dirk Ormoneit Institut fur Informatik (H2) Technische Universitat Munchen 80290 Munchen, Germany ormoneit@inJormatik.tu-muenchen.de Abstract Volker Tresp Siemens AG Central Research 81730 M... | 1995 | 78 |
1,126 | A Practical Monte Carlo Implementation of Bayesian Learning Carl Edward Rasmussen Department of Computer Science University of Toronto Toronto, Ontario, M5S 1A4, Canada carl@cs.toronto.edu Abstract A practical method for Bayesian training of feed-forward neural networks using sophisticated Mo... | 1995 | 79 |
1,127 | On the Computational Power of Noisy Spiking Neurons Wolfgang Maass Institute for Theoretical Computer Science, Technische Universitaet Graz Klosterwiesgasse 32/2, A-8010 Graz, Austria, e-mail: maass@igi.tu-graz.ac.at Abstract It has remained unknown whether one can in principle carry out reliable d... | 1995 | 8 |
1,128 | A Smoothing Regularizer for Recurrent Neural Networks Lizhong Wu and John Moody Oregon Graduate Institute, Computer Science Dept., Portland, OR 97291-1000 Abstract We derive a smoothing regularizer for recurrent network models by requiring robustness in prediction performance to perturbations of th... | 1995 | 80 |
1,129 | REMAP: Recursive Estimation and Maximization of A Posteriori Probabilities - Application to Transition-Based Connectionist Speech Recognition Yochai Konig, Herve Bourlard~ and Nelson Morgan {konig, bourlard,morgan }@icsi.berkeley.edu International Computer Science Institute 1947 Center Street Be... | 1995 | 81 |
1,130 | Harmony Networks Do Not Work Rene Gourley School of Computing Science Simon Fraser University Burnaby, B.C., V5A 1S6, Canada gourley@mprgate.mpr.ca Abstract Harmony networks have been proposed as a means by which connectionist models can perform symbolic computation. Indeed, proponents claim that a... | 1995 | 82 |
1,131 | Learning Sparse Perceptrons Jeffrey C. Jackson Mathematics & Computer Science Dept. Duquesne University 600 Forbes Ave Pittsburgh, PA 15282 jackson@mathcs.duq.edu Abstract Mark W. Craven Computer Sciences Dept. University of Wisconsin-Madison 1210 West Dayton St. Madison, WI 53706 ... | 1995 | 83 |
1,132 | The Role of Activity in Synaptic Competition at the Neuromuscular Junction Samuel R. H. Joseph Centre for Cognitive Science Edinburgh University Edinburgh, U.K. email: sam@cns.ed.ac.uk David J. Willshaw Centre for Cognitive Science Edinburgh University Edinburgh, U.K. email: david@cn... | 1995 | 84 |
1,133 |
! #" $ %'& !( ) * +-,/.103254 687:95,/;<0=43>3?@0BADC3E 7 ,503,GF50HJI<? ELKNM I ABOQP R 0=7:S:IT2 UWVX Y=Z=[]\_^W`3acb d \_e ac\ fg\@Y [ f \ Y [ Vihkjmli[]n \_o l []p ... | 1995 | 85 |
1,134 | Explorations with the Dynamic Wave Model Thomas P. Rebotier Department of Cognitive Science UCSD, 9500 Gilman Dr LA JOLLA CA 92093-0515 rebotier@cogsci.ucsd.edu Jeffrey L. Elman Department of Cognitive Science UCSD, 9500 Gilman Dr LA JOLLA CA 92093-0515 elman@cogsci.ucsd.edu Abstract... | 1995 | 86 |
1,135 | Generalization in Reinforcement Learning: Successful Examples Using Sparse Coarse Coding Richard S. Sutton University of Massachusetts Amherst, MA 01003 USA richOcs.umass.edu Abstract On large problems, reinforcement learning systems must use parameterized function approximators such as neural n... | 1995 | 87 |
1,136 | A Multiscale Attentional Framework for Relaxation Neural Networks Dimitris I. Tsioutsias Dept. of Electrical Engineering Yale University New Haven, CT 06520-8285 tsioutsias~cs.yale.edu Eric Mjolsness Dept. of Computer Science & Engineering University of California, San Diego La Jolla, CA 9... | 1995 | 88 |
1,137 | VLSI Model of Primate Visual Smooth Pursuit Ralph Etienne-Cummings Department of Electrical Engineering, Southern Illinois University, Carbondale, IL 62901 Jan Van der Spiegel Moore School of Electrical Engineering, University of Pennsylvania, Philadelphia, PA 19104 Paul Mueller Corticon, ... | 1995 | 89 |
1,138 | Parallel Optimization of Motion Controllers via Policy Iteration J. A. Coelho Jr., R. Sitaraman, and R. A. Grupen Department of Computer Science University of Massachusetts, Amherst, 01003 Abstract This paper describes a policy iteration algorithm for optimizing the performance of a harmonic functi... | 1995 | 9 |
1,139 | Reinforcement Learning by Probability Matching Philip N. Sabes sabes~psyche.mit.edu Michael I. Jordan jordan~psyche.mit.edu Department of Brain and Cognitive Sciences Massachusetts Institute of Technology Cambridge, MA 02139 Abstract We present a new algorithm for associative reinforcement... | 1995 | 90 |
1,140 | Generalized Learning Vector Quantization Atsushi Sato & Keiji Yamada Information Technology Research Laboratories, NEC Corporation 1-1, Miyazaki 4-chome, Miyamae-ku, Kawasaki, Kanagawa 216, Japan E-mail: {asato.yamada}@pat.cl.nec.co.jp Abstract We propose a new learning method, "Generalized L... | 1995 | 91 |
1,141 | Bayesian Methods for Mixtures of Experts Steve Waterhouse Cambridge University Engineering Department Cambridge CB2 1PZ England Tel: [+44] 1223 332754 srw1001@eng.cam.ac.uk David MacKay Cavendish Laboratory Madingley Rd. Cambridge CB3 OHE England Tel: [+44] 1223 337238 mackay@m... | 1995 | 92 |
1,142 | High-Speed Airborne Particle Monitoring Using Artificial Neural Networks Alistair Ferguson ERDC, Univ. of Hertfordshire A.Ferguson@herts.ac.uk Paul Kaye ERDC, Univ. of Hertfordshire Theo Sabisch Dept. Electrical and Electronic Eng. U niv. of Hertfordshire Laurence C. Dixon NOC, Univ. of... | 1995 | 93 |
1,143 | Adaptive Mixture of Probabilistic Transducers Yoram Singer AT&T Bell Laboratories singer@research.att.com Abstract We introduce and analyze a mixture model for supervised learning of probabilistic transducers. We devise an online learning algorithm that efficiently infers the structure and estimate... | 1995 | 94 |
1,144 | SEEMORE: A View-Based Approach to 3-D Object Recognition Using Multiple Visual Cues Bartlett W. Mel Department of Biomedical Engineering University of Southern California Los Angeles, CA 90089 mel@quake.usc.edu Abstract A neurally-inspired visual object recognition system is described call... | 1995 | 95 |
1,145 | Using Pairs of Data-Points to Define Splits for Decision Trees Geoffrey E. Hinton Department of Computer Science University of Toronto Toronto, Ontario, M5S lA4, Canada hinton@cs.toronto.edu Michael Revow Department of Computer Science University of Toronto Toronto, Ontario, M5S lA4, Canad... | 1995 | 96 |
1,146 | Dynamics of On-Line Gradient Descent Learning for Multilayer Neural Networks David Saad" Dept. of Compo Sci. & App. Math. Sara A. Solla t CONNECT, The Niels Bohr Institute Blegdamsdvej 17 Copenhagen 2100, Denmark Aston University Birmingham B4 7ET, UK Abstract We consider the problem of... | 1995 | 97 |
1,147 | Geometry of Early Stopping in Linear Networks Robert Dodier * Dept. of Computer Science University of Colorado Boulder, CO 80309 Abstract A theory of early stopping as applied to linear models is presented. The backpropagation learning algorithm is modeled as gradient descent in continuous ti... | 1995 | 98 |
1,148 | A Unified Learning Scheme: Bayesian-Kullback Ying-Yang Machine Lei Xu 1. Computer Science Dept., The Chinese University of HK, Hong Kong 2. National Machine Perception Lab, Peking University, Beijing Abstract A Bayesian-Kullback learning scheme, called Ying-Yang Machine, is proposed based on the tw... | 1995 | 99 |
1,149 | Hebb Learning of Features based on their Information Content Hideki Noda Ferdinand Peper Communications Research Laboratory 588-2, Iwaoka, Iwaoka-cho Nishi-ku, Kobe 651-24 Japan peper@crl.go.jp Kyushu Institute of Technology Dept. Electr., Electro., and Compo Eng. 1-1 Sensui-cho, Tobata... | 1996 | 1 |
1,150 | Source Separation and Density Estimation by Faithful Equivariant SOM Juan K. Lin Department of Physics University of Chicago Chicago, IL 60637 jk-lin@uchicago.edu David G. Grier Department of Physics University of Chicago Chicago, IL 60637 d-grier@uchicago.edu Abstract Jack D. Cow... | 1996 | 10 |
1,151 | Statistical Mechanics of the Mixture of Experts Kukjin Kang and Jong-Hoon Oh Department of Physics Pohang University of Science and Technology Hyoja San 31, Pohang, Kyongbuk 790-784, Korea E-mail: kkj.jhohOgalaxy.postech.ac.kr Abstract We study generalization capability of the mixture of experts... | 1996 | 100 |
1,152 | Predicting Lifetimes in Dynamically Allocated Memory David A. Cohn Adaptive Systems Group Harlequin, Inc. Menlo Park, CA 94025 cohn~harlequin.com Satinder Singh Department of Computer Science University of Colorado Boulder, CO 80309 baveja~cs.colorado.edu Abstract Predictions ofli... | 1996 | 101 |
1,153 | Reinforcement Learning for Mixed Open-loop and Closed-loop Control Eric A. Hansen, Andrew G. Barto, and Shlorno Zilberstein Department of Computer Science University of Massachusetts Amherst, MA 01003 {hansen.barto.shlomo }<Dcs.umass.edu Abstract Closed-loop control relies on sensory feedback th... | 1996 | 102 |
1,154 | Computing with infinite networks Christopher K. I. Williams Neural Computing Research Group Department of Computer Science and Applied Mathematics Aston University, Birmingham B4 7ET, UK c.k.i.williamsGaston.ac.nk Abstract For neural networks with a wide class of weight-priors, it can be shown t... | 1996 | 103 |
1,155 | Regression with Input-Dependent Noise: A Bayesian Treatment Christopher M. Bishop C.M.BishopGaston.ac.uk Cazhaow S. Qazaz qazazcsGaston.ac.uk Neural Computing Research Group Aston University, Birmingham, B4 7ET, U.K. http://www.ncrg.aston.ac.uk/ Abstract In most treatments of the regressio... | 1996 | 104 |
1,156 | The Generalisation Cost of RAMnets Richard Rohwer and Michal Morciniec rohwerrj~cs.aston.ac.uk morcinim~cs.aston.ac.uk Neural Computing Research Group Aston University Aston Triangle, Birmingham B4 7ET, UK. Abstract Given unlimited computational resources, it is best to use a criterion of minima... | 1996 | 105 |
1,157 | Multilayer neural networks: one or two hidden layers? G. Brightwell Dept of Mathematics LSE, Houghton Street London WC2A 2AE, U.K. c. Kenyon, H. Paugam-Moisy LIP, URA 1398 CNRS ENS Lyon, 46 alIee d'Italie F69364 Lyon cedex, FRANCE Abstract We study the number of hidden layers required b... | 1996 | 106 |
1,158 | Improving the Accuracy and Speed of Support Vector Machines Chris J.C. Burges Bell Laboratories Lucent Technologies, Room 3G429 101 Crawford's Corner Road Holmdel, NJ 07733-3030 burges@bell-Iabs.com Abstract Bernhard Scholkopf" Max-Planck-Institut fur biologische Kybernetik, Spemanns... | 1996 | 107 |
1,159 | Adaptive Access Control Applied to Ethernet Data Timothy X Brown Dept. of Electrical and Computer Engineering University of Colorado, Boulder, CO 80309-0530 timxb@colorado.edu Abstract This paper presents a method that decides which combinations of traffic can be accepted on a packet data link, so ... | 1996 | 108 |
1,160 | An Adaptive WTA using Floating Gate Technology w. Fritz Kruger, Paul Hasler, Bradley A. Minch, and Christ of Koch California Institute of Technology Pasadena, CA 91125 (818) 395 - 2812 stretch@klab.caltech.edu Abstract We have designed, fabricated, and tested an adaptive WinnerTake-All (WTA) cir... | 1996 | 109 |
1,161 | Continuous sigmoidal belief networks trained using slice sampling Brendan J. Frey Department of Computer Science, University of Toronto 6 King's College Road, Toronto, Canada M5S 1A4 Abstract Real-valued random hidden variables can be useful for modelling latent structure that explains correlations... | 1996 | 11 |
1,162 | Representation and Induction of Finite State Machines using Time-Delay Neural Networks Daniel S. Clouse Computer Science & Engineering Dept. C. Lee Giles NEC Research Institute 4 Independence Way Princeton, NJ 08540 giles@research.nj .nec.com University of California, San Diego La Jolla... | 1996 | 110 |
1,163 | Probabilistic Interpretation of Population Codes Richard S. Zemel Peter Dayan zemeleu.arizona.edu dayaneai.mit.edu Abstract Alexandre Pouget alexesalk.edu We present a theoretical framework for population codes which generalizes naturally to the important case where the population provides... | 1996 | 111 |
1,164 | Analog VLSI Circuits for Attention-Based, Visual Tracking Timothy K. Horiuchi Computation and Neural Systems California Institute of Technology Pasadena, CA 91125 timmer@klab.caltech.edu Christof Koch Computation and Neural Systems California Institute of Technology Pasadena, CA 91125 T... | 1996 | 112 |
1,165 | Online learning from finite training sets: An analytical case study Peter Sollich* Department of Physics University of Edinburgh Edinburgh EH9 3JZ, U.K. P.SollichOed.ac.uk David Barbert Neural Computing Research Group Department of Applied Mathematics Aston University Birmingham B4 7ET,... | 1996 | 113 |
1,166 | Spatiotemporal Coupling and Scaling of Natural Images and Human Visual Sensitivities Dawei W. Dong California Institute of Technology Mail Code 139-74 Pasadena, CA 91125 dawei@hope.caltech.edu Abstract We study the spatiotemporal correlation in natural time-varying images and explore the h... | 1996 | 114 |
1,167 | U sing Curvature Information for Fast Stochastic Search Genevieve B. Orr Dept of Computer Science Willamette University 900 State Street Salem, OR 97301 gorr@willamette.edu Todd K. Leen Dept of Computer Science and Engineering Oregon Graduate Institute of Science and Technology P.O.B... | 1996 | 115 |
1,168 | ARC-LH: A New Adaptive Resampling Algorithm for Improving ANN Classifiers Friedrich Leisch Friedrich.Leisch@ci.tuwien.ac.at Kurt Hornik Kurt.Hornik@ci.tuwien.ac.at Institut fiir Statistik und Wahrscheinlichkeitstheorie Technische UniversWit Wien A-I040 Wien, Austria Abstract We introduce a... | 1996 | 116 |
1,169 | Estimating Equivalent Kernels For Neural Networks: A Data Perturbation Approach A. Neil Burgess Department of Decision Science London Business School London, NW1 4SA, UK (N.Burgess@lbs.lon.ac.uk) ABSTRACT We describe the notion of "equivalent kernels" and suggest that this provides a framewor... | 1996 | 117 |
1,170 | Monotonicity Hints Joseph Sill Computation and Neural Systems program California Institute of Technology email: joe@cs.caltech.edu Abstract Yaser S. Abu-Mostafa EE and CS Deptartments California Institute of Technology email: yaser@cs.caltech.edu A hint is any piece of side information abo... | 1996 | 118 |
1,171 | A Convergence Proof for the Softassign Quadratic Assignment Algorithm Anand Rangarajan Department of Diagnostic Radiology Yale University School of Medicine New Haven, CT 06520-8042 e-mail: anand<Onoodle. med. yale. edu Alan Yuille Smith-Kettlewell Eye Institute 2232 Webster Street San Fra... | 1996 | 119 |
1,172 | Compositionality, MDL Priors, and Object Recognition Elie Bienenstock (elie@dam.brown.edu) Stuart Geman (geman@dam.brown.edu) Daniel Potter (dfp@dam.brown.edu) Division of Applied Mathematics, Brown University, Providence, RI 02912 USA Abstract Images are ambiguous at each of many levels of a co... | 1996 | 12 |
1,173 | Removing Noise in On-Line Search using Adaptive Batch Sizes Genevieve B. Orr Department of Computer Science Willamette University 900 State Street Salem, Oregon 97301 gorr@willamette.ed-u Abstract Stochastic (on-line) learning can be faster than batch learning. However, at late times, the ... | 1996 | 120 |
1,174 | Size of multilayer networks for exact learning: analytic approach Andre Elisseefl' D~pt Mathematiques et Informatique Ecole Normale Superieure de Lyon 46 allee d'Italie F69364 Lyon cedex 07, FRANCE Helene Paugam-Moisy LIP, URA 1398 CNRS Ecole Normale Superieure de Lyon 46 allee d'Italie ... | 1996 | 121 |
1,175 | Support Vector Regression Machines Harris Drucker· Chris J.C. Burges" Linda Kaufman" Alex Smola·· Vladimir Vapoik + *Bell Labs and Monmouth University Department of Electronic Engineering West Long Branch. NJ 07764 **BellLabs + AT&T Labs Abstract A new regression technique based on V... | 1996 | 122 |
1,176 | An Hierarchical Model of Visual Rivalry Peter Dayan Department of Brain and Cognitive Sciences E25-21O Massachusetts Institute of Technology Cambridge, MA 02139 dayan@psyche.mit.edu1 Abstract Binocular rivalry is the alternating percept that can result when the two eyes see different scenes. Rec... | 1996 | 123 |
1,177 | Dynamically Adaptable CMOS Winner-Take-AII Neural Network Kunihiko Iizuka, Masayuki Miyamoto and Hirofumi Matsui Information Technology Research Laboratories Sharp Tenri, Nara, lAP AN Abstract The major problem that has prevented practical application of analog neuro-LSIs has been poor accuracy ... | 1996 | 124 |
1,178 | Ensemble Methods for Phoneme Classification Steve Waterhouse Gary Cook Cambridge University Engineering Department Cambridge CB2 IPZ, England, Tel: [+44] 1223 332754 Email: srwl00l@eng.cam.ac.uk.gdc@eng.cam.ac.uk Abstract This paper investigates a number of ensemble methods for improving the per... | 1996 | 125 |
1,179 | Maximum Likelihood Blind Source Separation: A Context-Sensitive Generalization of ICA Barak A. Pearlmutter Computer Science Dept, FEC 313 University of New Mexico Albuquerque, NM 87131 bap@cs.unm.edu Abstract Lucas C. Parra Siemens Corporate Research 755 College Road East Princeton, ... | 1996 | 126 |
1,180 | Temporal Low-Order Statistics of Natural Sounds H. Attias· and C.E. Schreinert Sloan Center for Theoretical Neurobiology and W.M. Keck Foundation Center for Integrative Neuroscience University of California at San Francisco San Francisco, CA 94143-0444 Abstract In order to process incoming sound... | 1996 | 127 |
1,181 | Limitations of self-organizing maps for vector quantization and multidimensional scaling Arthur Flexer The Austrian Research Institute for Artificial Intelligence Schottengasse 3, A-lOlO Vienna, Austria and Department of Psychology, University of Vienna Liebiggasse 5, A-lOlO Vienna, Austria a... | 1996 | 128 |
1,182 | A spike based learning neuron in analog VLSI Philipp Hiifliger Institute of Neuroinformatics ETHZjUNIZ Gloriastrasse 32 CH-8006 Zurich Switzerland e-mail: haftiger@neuroinf.ethz.ch tel: ++41 1 257 26 84 Misha Mahowald Institute of Neuroinformatics ETHZjUNIZ Gloriastrasse 32 CH-... | 1996 | 129 |
1,183 | A mean field algorithm for Bayes learning in large feed-forward neural networks Manfred Opper Institut fur Theoretische Physik Julius-Maximilians-Universitat, Am Hubland D-97074 Wurzburg, Germany opperOphysik.Uni-Wuerzburg.de Abstract Ole Winther CONNECT The Niels Bohr Institute Blegdam... | 1996 | 13 |
1,184 | One-unit Learning Rules for Independent Component Analysis Aapo Hyvarinen and Erkki Oja Helsinki University of Technology Laboratory of Computer and Information Science Rakentajanaukio 2 C, FIN-02150 Espoo, Finland email: {Aapo.Hyvarinen.Erkki.Oja}(Qhut.fi Abstract Neural one-unit learning rules... | 1996 | 130 |
1,185 | Analysis of Temporal-Difference Learning with Function Approximation John N. Tsitsiklis and Benjamin Van Roy Laboratory for Information and Decision Systems Massachusetts Institute of Technology Cambridge, MA 02139 e-mail: jnt@mit.edu, bvr@mit.edu Abstract We present new results about the tempor... | 1996 | 131 |
1,186 | Fast Network Pruning and Feature Extraction Using the Unit-OBS Algorithm Achim Stahlberger and Martin Riedmiller Institut fur Logik, Komplexitiit und Deduktionssysteme Universitiit Karlsruhe, 76128 Karlsruhe, Germany email: stahlb@ira.uka.de. riedml@ira.uka.de Abstract The algorithm described in th... | 1996 | 132 |
1,187 | Learning with Noise and Regularizers Multilayer Neural Networks David Saad Dept. of Compo Sci. & App. Math. Aston University Birmingham B4 7ET, UK D .Saad@aston.ac.uk Abstract Sara A. Solla AT &T Research Labs Holmdel, NJ 07733, USA solla@research .at t .com We study the effect of no... | 1996 | 133 |
1,188 | The Learning Dynamics of a Universal Approximator Ansgar H. L. West1,2 A.H.L.West~aston.ac.uk David Saad1 D.Saad~aston.ac.uk Ian T. N abneyl I.T.Nabney~aston.ac.uk 1 Neural Computing Research Group, University of Aston Birmingham B4 7ET, U.K. http://www.ncrg.aston.ac.uk/ 2Department of ... | 1996 | 134 |
1,189 | Gaussian Processes for Bayesian Classification via Hybrid Monte Carlo David Barber and Christopher K. I. Williams Neural Computing Research Group Department of Computer Science and Applied Mathematics Aston University, Birmingham B4 7ET, UK d.barber~aston.ac.uk c.k.i.williams~aston.ac.uk Abstrac... | 1996 | 135 |
1,190 | Genetic Algorithms and Explicit Search Statistics Shumeet 8a1uja baluja@cs.cmu.edu Justsystem Pittsburgh Research Center & School of Computer Science, Carnegie Mellon University Abstract The genetic algorithm (GA) is a heuristic search procedure based on mechanisms abstracted from population geneti... | 1996 | 136 |
1,191 | .. Learning Exact Patterns of Quasi-synchronization among Spiking Neurons from Data on Multi-unit Recordings Laura Martignon Max Planck Institute for Psychological Research Adaptive Behavior and Cognition 80802 Munich, Germany laura@mpipf-muenchen.mpg.de Gustavo Deco Siemens AG Centr... | 1996 | 137 |
1,192 | Efficient Nonlinear Control with Actor-Tutor Architecture Kenji Doya* A.TR Human Information Processing Research Laboratories 2-2 Hikaridai, Seika-cho, Soraku-gun, Kyoto 619-02, Japan. Abstract A new reinforcement learning architecture for nonlinear control is proposed. A direct feedback controller... | 1996 | 138 |
1,193 | Interpolating Earth-science Data using RBF Networks and Mixtures of Experts E.VVan D.Bone Division of Infonnation Technology Canberra Laboratory, CSIRO GPO Box 664, Canberra, ACT, 2601, Australia {ernest, don} @cbr.dit.csiro.au Abstract We present a mixture of experts (ME) approach to interpo... | 1996 | 139 |
1,194 | Ordered Classes and Incomplete Examples in Classification Mark Mathieson Department of Statistics, University of Oxford 1 South Parks Road, Oxford OXI 3TG, UK E-mail: mathies@stats.ox.ac.uk Abstract The classes in classification tasks often have a natural ordering, and the training and testing e... | 1996 | 14 |
1,195 | Statistically Efficient Estimation Using Cortical Lateral Connections Alexandre Pouget alex@salk.edu Abstract Kechen Zhang zhang@salk.edu Coarse codes are widely used throughout the brain to encode sensory and motor variables. Methods designed to interpret these codes, such as population vector ... | 1996 | 140 |
1,196 | Recursive algorithms for approximating probabilities in graphical models Tommi S. Jaakkola and Michael I. Jordan {tommi,jordan}Opsyche.mit.edu Department of Brain and Cognitive Sciences Massachusetts Institute of Technology Cambridge, MA 02139 Abstract We develop a recursive node-elimination for... | 1996 | 141 |
1,197 | Clustering via Concave Minimization P. S. Bradley and O. L. Mangasarian Computer Sciences Department University of Wisconsin 1210 West Dayton Street Madison, WI 53706 email: paulb@es.wise.edu, olvi@es.wise.edu Abstract w. N. Street Computer Science Department Oklahoma State University 2... | 1996 | 142 |
1,198 | Balancing between bagging and bumping Tom Heskes RWCP Novel Functions SNN Laboratory; University of Nijmegen Geert Grooteplein 21, 6525 EZ Nijmegen, The Netherlands tom@mbfys.kun.nl Abstract We compare different methods to combine predictions from neural networks trained on different bootstrap samples... | 1996 | 143 |
1,199 | Self-Organizing and Adaptive Algorithms for Generalized Eigen-Decomposition Chanchal Chatterjee Newport Corporation 1791 Deere Avenue, Irvine, CA 92606 Vwani P. Roychowdhury Electrical Engineering Department UCLA, Los Angeles, CA 90095 ABSTRACT The paper is developed in two parts where we dis... | 1996 | 144 |
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