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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900 | Grammar Learning by a Self-Organizing Network Michiro Negishi Dept. of Cognitive and Neural Systems, Boston University 111 Cummington Street Boston, MA 02215 email: negishi@cns.bu.edu Abstract This paper presents the design and simulation results of a selforganizing neural network which induces a g... | 1994 | 138 |
901 | Coarse-to-Fine Image Search Using Neural Networks Clay D. Spence, John C. Pearson, and Jim Bergen Nationallnfonnation Display Laboratory P.O. Box 8619 Princeton, NJ 08543-8619 cspence@sarnoff.com John_Pearson@maca.sarnoff.com jbergen@sarnoff.com Abstract The efficiency of image search can ... | 1994 | 139 |
902 | Predicting the Risk of Complications in Coronary Artery Bypass Operations using Neural Networks Richard P. Lippmann, Linda Kukolich MIT Lincoln Laboratory 244 Wood Street Lexington, MA 02173-0073 Abstract Dr. David Shahian Lahey Clinic Burlington, MA 01805 Experiments demonstrated that sig... | 1994 | 14 |
903 | ICEG Morphology Classification using an Analogue VLSI Neural Network Richard Coggins, Marwan Jabri, Barry Flower and Stephen Pickard Systems Engineering and Design Automation Laboratory Department of Electrical Engineering J03, University of Sydney, 2006, Australia. Email: richardc@sedal.su.oz.au A... | 1994 | 140 |
904 | Spatial Representations in the Parietal Cortex May Use Basis Functions Alexandre Pouget alex@salk.edu Terrence J. Sejnowski terry@salk.edu Howard Hughes Medical Institute The Salk Institute La Jolla, CA 92037 and Department of Biology University of California, San Diego Abstract T... | 1994 | 15 |
905 | Reinforcement Learning Algorithm for Partially Observable Markov Decision Problems Tommi Jaakkola tommi@psyche.mit.edu Satinder P. Singh singh@psyche.mit.edu Michael I. Jordan jordan@psyche.mit.edu Department of Brain and Cognitive Sciences, BId. E10 Massachusetts Institute of Technology ... | 1994 | 16 |
906 | FINANCIAL APPLICATIONS OF LEARNING FROM HINTS Yaser s. Abu-Mostafa California Institute of Technology and NeuroDollars, Inc. e-mail: yaser@caltech.edu Abstract The basic paradigm for learning in neural networks is 'learning from examples' where a training set of input-output examples is used ... | 1994 | 17 |
907 | An Auditory Localization and Coordinate Transform Chip Timothy K. Horiuchi timmer@cns.caltech.edu Computation and Neural Systems Program California Institute of Technology Pasadena, CA 91125 Abstract The localization and orientation to various novel or interesting events in the environment is... | 1994 | 18 |
908 | Limits on Learning Machine Accuracy Imposed by Data Quality Corinna Cortes, L. D. Jackel, and Wan-Ping Chiang AT&T Bell Laboratories Holmdel, NJ 07733 Abstract Random errors and insufficiencies in databases limit the performance of any classifier trained from and applied to the database. In this pa... | 1994 | 19 |
909 | A Model of the Neural Basis of the Rat's Sense of Direction William E. Skaggs James J. Knierim bill@nsma.arizona. edu jim@nsma.arizona. edu Hemant S. Kudrimoti hemant@nsma. arizona. edu Bruce L. McNaughton bruce@nsma. arizona. edu ARL Division of Neural Systems, Memory, And Aging 344 Li... | 1994 | 2 |
910 | Interference in Learning Internal Models of Inverse Dynamics in Humans Reza Shadmehr; Tom Brashers-Krug, and Ferdinando Mussa-lvaldit Dept. of Brain and Cognitive Sciences M. I. T., Cambridge, MA 02139 reza@bme.jhu.edu, tbk@ai.mit.edu, sandro@parker.physio.nwu.edu Abstract Experiments were performe... | 1994 | 20 |
911 | Optimal Movement Primitives Terence D. Sanger Jet Propulsion Laboratory MS 303-310 4800 Oak Grove Drive Pasadena, CA 91109 (818) 354-9127 tds@ai.mit.edu Abstract The theory of Optimal Unsupervised Motor Learning shows how a network can discover a reduced-order controller for an unknown non... | 1994 | 21 |
912 | Using a Saliency Map for Active Spatial Selective Attention: Implementation & Initial Results Shumeet Baluja baluja@cs.cmu.edu School of Computer Science Carnegie Mellon University Pittsburgh, PA 15213 Abstract Dean A. Pomerleau pomerleau@cs.cmu.edu School of Computer Science Carnegie M... | 1994 | 22 |
913 | Factorial Learning and the EM Algorithm Zoubin Ghahramani zoubin@psyche.mit.edu Department of Brain & Cognitive Sciences Massachusetts Institute of Technology Cambridge, MA 02139 Abstract Many real world learning problems are best characterized by an interaction of multiple independent causes or... | 1994 | 23 |
914 | Pairwise Neural Network Classifiers with Probabilistic Outputs David Price A2iA and ESPCI 3 Rue de l'Arrivee, BP 59 75749 Paris Cedex 15, France a2ia@dialup.francenet.fr Stefan Knerr ESPCI and CNRS (UPR AOOO5) 10, Rue Vauquelin, 75005 Paris, France knerr@neurones.espci.fr Leon Personnaz... | 1994 | 24 |
915 | Real-Time Control of a Tokamak Plasma Using Neural Networks Chris M Bishop Neural Computing Research Group Department of Computer Science Aston University Birmingham, B4 7ET, U.K. c.m.bishop@aston.ac.uk Paul S Haynes, Mike E U Smith, Tom N Todd, David L Trotman and Colin G Windsor AEA Tech... | 1994 | 25 |
916 | An Actor/Critic Algorithm that Equivalent to Q-Learning • IS Robert H. Crites Computer Science Department University of Massachusetts Amherst, MA 01003 crites~cs.umass.edu Andrew G. Barto Computer Science Department University of Massachusetts Amherst, MA 01003 barto~cs.umass.edu ... | 1994 | 26 |
917 | Template-Based Algorithms for Connectionist Rule Extraction Jay A. Alexander and Michael C. Mozer Department of Computer Science and Institute for Cognitive Science University of Colorado Boulder, CO 80309--0430 Abstract Casting neural network weights in symbolic terms is crucial for interpre... | 1994 | 27 |
918 | Reinforcement Learning with Soft State Aggregation Satinder P. Singh Tommi Jaakkola Michael I. Jordan singh@psyche.mit.edu tommi@psyche.mit.edu jordan@psyche.mit.edu Dept. of Brain & Cognitive Sciences (E-lO) M.I.T. Cambridge, MA 02139 Abstract It is widely accepted that the use of m... | 1994 | 28 |
919 | A Connectionist Technique for Accelerated Textual Input: Letting a Network Do the Typing Dean A. Pomerleau pomerlea@cs.cmu.edu School of Computer Science Carnegie Mellon University Pittsburgh, PA 15213 Abstract Each year people spend a huge amount of time typing. The text people type typicall... | 1994 | 29 |
920 | A Mixture Model System for Medical and Machine Diagnosis Magnus Stensmo Terrence J. Sejnowski Computational Neurobiology Laboratory The Salk Institute for Biological Studies 10010 North Torrey Pines Road La Jolla, CA 92037, U.S.A. {magnus,terry}~salk.edu Abstract Diagnosis of human disease... | 1994 | 3 |
921 | Advantage Updating Applied to a Differential Game Mance E. Harmon Wright Laboratory WL/AAAT Bldg. 635 2185 Avionics Circle Wright-Patterson Air Force Base, OH 45433-7301 harmonme@aa.wpafb.mil A. Harry Klopr Wright Laboratory klopfah@aa.wpafb.mil Leemon C. Baird III· Wright Laboratory ... | 1994 | 30 |
922 | Pattern Playback in the '90s Malcolm Slaney Interval Research Corporation 180 l-C Page Mill Road, Palo Alto, CA 94304 malcolm@interval.com Abstract Deciding the appropriate representation to use for modeling human auditory processing is a critical issue in auditory science. While engineers have ... | 1994 | 31 |
923 | An Analog Neural Network Inspired by Fractal Block Coding Fernando J. Pineda The Applied Physics Laboratory The Johns Hopkins University Johns Hokins Road Laurel, MD 20723-6099 Andreas G. Andreou Dept. of Electrical & Computer Engineering The Johns Hopkins University 34th & Charles St. ... | 1994 | 32 |
924 | Phase-Space Learning Fu-Sheng Tsung Chung Tai Ch'an Temple 56, Yuon-fon Road, Yi-hsin Li, Pu-li Nan-tou County, Taiwan 545 Republic of China Garrison W. Cottrell· Institute for Neural Computation Computer Science & Engineering University of California, San Diego La Jolla, California 92093 ... | 1994 | 33 |
925 | An experimental comparison of recurrent neural networks Bill G. Horne and C. Lee Giles· NEe Research Institute 4 Independence Way Princeton, NJ 08540 {horne.giles}~research.nj.nec.com Abstract Many different discrete-time recurrent neural network architectures have been proposed. However, there ... | 1994 | 34 |
926 | Inferring Ground Truth from Subjective Labelling of Venus Images Padhraic Smyth, Usama Fayyad Jet Propulsion Laboratory 525-3660, Caltech, 4800 Oak Grove Drive, Pasadena, CA 91109 Michael Burl, Pietro Perona Department of Electrical Engineering Caltech, MS 116-81, Pasadena, CA 91125 Pierre... | 1994 | 35 |
927 | Learning Prototype Models for Tangent Distance Trevor Hastie· Statistics Department Sequoia Hall Stanford University Stanford, CA 94305 email: trevor@playfair .stanford .edu Patrice Simard AT&T Bell Laboratories Crawfords Corner Road Holmdel, NJ 07733 email: patrice@neural.att.com ... | 1994 | 36 |
928 | Diffusion of Credit in Markovian Models Yoshua Bengio· Dept. I.R.O., Universite de Montreal, Montreal, Qc, Canada H3C-3J7 bengioyCIRO.UMontreal.CA Paolo Frasconi Dipartimento di Sistemi e Informatica Universita di Firenze, Italy paoloCmcculloch.ing.unifi.it Abstract This paper studies the ... | 1994 | 37 |
929 | The NilOOO: High Speed Parallel VLSI for Implementing Multilayer Perceptrons Leon N Cooper Michael P. Perrone Thomas J. Watson Research Center P.O. Box 704 Yorktown Heights, NY 10598 mppGwatson.ibm.com Institute for Brain and Neural Systems Brown University Providence, Ri 02912 IncGcns.... | 1994 | 38 |
930 | Model of a Biological Neuron as a Temporal Neural Network Sean D. Murphy and Edward W. Kairiss Interdepartmental Neuroscience Program, Department of Psychology, and The Center for Theoretical and Applied Neuroscience, Yale University, Box 208205, New Haven, CT 06520 Abstract A biological neuron ... | 1994 | 39 |
931 | Learning with Preknowledge: Clustering with Point and Graph Matching Distance Measures Steven Gold!, Anand Rangarajan1 and Eric Mjolsness2 Department of Computer Science Yale University New Haven, CT 06520-8285 Abstract Prior constraints are imposed upon a learning problem in the form of dist... | 1994 | 4 |
932 | Non-linear Prediction of Acoustic Vectors Using Hierarchical Mixtures of Experts S.R.Waterhouse A.J.Robinson Cambridge University Engineering Department, Trumpington St., Cambridge, CB2 1PZ, England. Tel: [+44] 223 332800, Fax: [+44] 223 332662, Email: srwlO01.ajr@eng.cam.ac.uk URL: http://svr-w... | 1994 | 40 |
933 | JPMAX: Learning to Recognize Moving Objects as a Model-fitting Problem Suzanna Becker Department of Psychology, McMaster University Hamilton, Onto L8S 4K1 Abstract Unsupervised learning procedures have been successful at low-level feature extraction and preprocessing of raw sensor data. So far, ... | 1994 | 41 |
934 | The Electrotonic Transformation: a Tool for Relating Neuronal Form to Function Nicholas T. Carnevale Department of Psychology Yale University New Haven, CT 06520 Brenda J. Claiborne Division of Life Sciences University of Texas San Antonio, TX 79285 Abstract Kenneth Y. Tsai Departmen... | 1994 | 42 |
935 | Reinforcement Learning Predicts the Site of Plasticity for Auditory Remapping in the Barn Owl Alexandre Pougett alex@salk.edu Cedric Deffayett Terrence J. Sejnowskit cedric@salk.edu terry@salk.edu tHoward Hughes Medical Institute The Salk Institute La Jolla, CA 92037 Department of Bi... | 1994 | 43 |
936 | Boltzmann Chains and Hidden Markov Models Lawrence K. Saul and Michael I. Jordan lksaulOpsyche.mit.edu, jordanOpsyche.mit.edu Center for Biological and Computational Learning Massachusetts Institute of Technology 79 Amherst Street, E10-243 Cambridge, MA 02139 Abstract We propose a statistical... | 1994 | 44 |
937 | Comparing the prediction accuracy of artificial neural networks and other statistical models for breast cancer survival Harry B. Burke Department of Medicine New York Medical College Valhalla, NY 10595 David B. Rosen Department of Medicine New York Medical College Valhalla, NY 10595 ... | 1994 | 45 |
938 | Efficient Methods for Dealing with Missing Data in Supervised Learning Volker '!'resp· Siemens AG Central Research Otto-Hahn-Ring 6 81730 Miinchen Germany Ralph Neuneier Siemens AG Central Research Otto-Hahn-Ring 6 81730 Miinchen Germany Abstract Subutai Ahmad Interval Re... | 1994 | 46 |
939 | PREDICTIVE CODING WITH NEURAL NETS: APPLICATION TO TEXT COMPRESSION J iirgen Schmidhuber Fakultat fiir Informatik Technische Universitat Miinchen 80290 Miinchen, Germany Abstract Stefan Heil To compress text files, a neural predictor network P is used to approximate the conditional probabilit... | 1994 | 47 |
940 | Computational structure of coordinate transformations: A generalization study Zoubin Ghahramani zoubin@psyche.mit.edu Daniel M. Wolpert wolpert@psyche.mit.edu Michael I. Jordan jordan@psyche.mit.edu Department of Brain & Cognitive Sciences Massachusetts Institute of Technology Cambridge, M... | 1994 | 48 |
941 | Recognizing Handwritten Digits Using Mixtures of Linear Models Geoffrey E Hinton Michael Revow Peter Dayan Deparbnent of Computer Science, University of Toronto Toronto, Ontario, Canada M5S lA4 Abstract We construct a mixture of locally linear generative models of a collection of pixel-based images... | 1994 | 49 |
942 | Learning Local Error Bars for Nonlinear Regression David A.Nix Department of Computer Science and Institute of Cognitive Science University of Colorado Boulder, CO 80309-0430 dnix@cs.colorado.edu Andreas S. Weigend Department of Computer Science and Institute of Cognitive Science Univer... | 1994 | 5 |
943 | A Critical Comparison of Models for Orientation and Ocular Dominance Columns in the Striate Cortex E. Erwin Beckman Institute University of Illinois Urbana, IL 61801, USA K. Obermayer Technische Fakultat U niversitat Bielefeld 33615 Bielefeld, FRG Abstract K. Schulten Beckman Inst... | 1994 | 50 |
944 | Classifying with Gaussian Mixtures and Clusters Nanda Kambhatla and Todd K. Leen Department of Computer Science and Engineering Oregon Graduate Institute of Science & Technology P.O. Box 91000 Portland, OR 97291-1000 nanda@cse.ogi.edu, tleen@cse.ogi.edu Abstract In this paper, we derive classifi... | 1994 | 51 |
945 | Anatomical origin and computational role of diversity in the response properties of cortical neurons Kalanit Grill Spectort Shimon Edelmant Rafael Malacht Depts of t Applied Mathematics and Computer Science and tN eurobiology The Weizmann Institute of Science Rehovot 76100, Israel {kalanit.ed... | 1994 | 52 |
946 | Synchrony and Desynchrony in Neural Oscillator Networks DeLiang Wang Department of Computer and Information Science and Center for Cognitive Science The Ohio State University Columbus, Ohio 43210, USA dwang@cis.ohio-state.edu Abstract David Terman Department of Mathematics The Ohio Stat... | 1994 | 53 |
947 | A Computational Model of Prefrontal Cortex Function Todd S. Braver Dept. of Psychology Carnegie Mellon Univ. Pittsburgh, PA 15213 Jonathan D. Cohen Dept. of Psychology Carnegie Mellon Univ. Pittsburgh, PA 15213 Abstract David Servan-Schreiber Dept. of Psychiatry Univ . of Pittsbur... | 1994 | 54 |
948 | Combining Estimators Using Non-Constant Weighting Functions Volker Tresp*and Michiaki Taniguchi Siemens AG, Central Research Otto-Hahn-Ring 6 81730 Miinchen, Germany Abstract This paper discusses the linearly weighted combination of estimators in which the weighting functions are dependent on the i... | 1994 | 55 |
949 | Stochastic Dynamics of Three-State Neural Networks Toru Ohira Sony Computer Science Laboratory 3-14-13 Higashi-gotanda, Tokyo 141, Japan ohira@csl.sony.co.jp Jack D. Cowan Depts. of Mathematics and Neurology University of Chicago Chicago, IL 60637 cowan@synapse.uchicago.edu Abstract ... | 1994 | 56 |
950 | On the Computational Utility of Consciousness Donald W. Mathis and Michael C. Mozer mathis@cs.colorado.edu, mozer@cs.colorado.edu Department of Computer Science and Institute of Cognitive Science University of Colorado, Boulder Boulder, CO 80309-0430 Abstract We propose a computational framework... | 1994 | 57 |
951 | Ocular Dominance and Patterned Lateral Connections in a Self-Organizing Model of the Primary Visual Cortex Joseph Sirosh and Risto Miikkulainen Department of Computer Sciences University of Texas at Austin, Austin, 'IX 78712 email: sirosh.risto~cs.utexas.edu Abstract A neural network model for t... | 1994 | 58 |
952 | Effects of Noise on Convergence and Generalization in Recurrent Networks Kam Jim Bill G. Horne c. Lee Giles* NEC Research Institute, Inc., 4 Independence Way, Princeton, NJ 08540 {kamjim,horne,giles}~research.nj.nec.com *Also with UMIACS, University of Maryland, College Park, MD 20742 Abstrac... | 1994 | 59 |
953 | Reinforcement Learning Methods for Continuous-Time Markov Decision Problems Steven J. Bradtke Computer Science Department University of Massachusetts Amherst, MA 01003 bradtkeGcs.umass.edu Michael O. Duff Computer Science Department University of Massachusetts Amherst, MA 01003 duffG... | 1994 | 6 |
954 | An Integrated Architecture of Adaptive Neural Network Control for Dynamic Systems Robert L. Tokar2 Brian D.McVey2 'Center for Nonlinear Studies, 2Applied Theoretical Physics Division Los Alamos National Laboratory, Los Alamos, NM, 87545 Abstract In this study, an integrated neural network contro... | 1994 | 60 |
955 | Implementation of Neural Hardware with the Neural VLSI of URAN in Applications with Reduced Representations ll-Song Han Korea Telecom Research Laboratories 17, Woomyun-dong, Suhcho-ku Seoul 137-140, KOREA Hwang-Soo Lee Dept. of Info and Comm KAIST Seoul, 130-012, Korea Abstract Ki-Ch... | 1994 | 61 |
956 | Estimating Conditional Probability Densities for Periodic Variables Chris M Bishop and Claire Legleye Neural Computing Research Group Department of Computer Science and Applied Mathematics Aston University Birmingham, B4 7ET, U.K. c.m.bishop@aston.ac.uk Abstract Most of the common techniques ... | 1994 | 62 |
957 | Analysis of Unstandardized Contributions in Cross Connected Networks Thomas R. Shultz shultz@psych.mcgill.ca Yuriko Oshima-Takane yuriko@psych.mcgill.ca Department of Psychology McGill University Montreal, Quebec, Canada H3A IBI Abstract Yoshio Takane takane@psych.mcgill.ca Understan... | 1994 | 63 |
958 | A Rigorous Analysis Of Linsker-type Hebbian Learning J. Feng Mathematical Department University of Rome "La Sapienza» P. Ie A. Moro, 00185 Rome, Italy feng~at.uniroma1.it H. Pan V. P. Roychowdhury School of Electrical Engineering Purdue University West Lafayette, IN 47907 hpan~ecn.pu... | 1994 | 64 |
959 | Associative Decorrelation Dynamics: A Theory of Self-Organization and Optimization in Feedback Networks Dawei W. Dong* Lawrence Berkeley Laboratory University of California Berkeley, CA 94720 Abstract This paper outlines a dynamic theory of development and adaptation in neural networks with feed... | 1994 | 65 |
960 | Visual Speech Recognition with Stochastic Networks Javier R. Movellan Department of Cognitive Science University of California San Diego La Jolla, Ca 92093-0515 Abstract This paper presents ongoing work on a speaker independent visual speech recognition system. The work presented here builds on ... | 1994 | 66 |
961 | Finding Structure in Reinforcement Learning Sebastian Thrun University of Bonn Department of Computer Science nr R6merstr. 164, D-53117 Bonn, Germany E-mail: thrun@carbon.informatik.uni-bonn.de Abstract Anton Schwartz Dept. of Computer Science Stanford University Stanford, CA 94305 Emai... | 1994 | 67 |
962 | Active Learning with Statistical Models David A. Cohn, Zoubin Ghahramani, and Michael I. Jordan cohnQpsyche.mit.edu. zoubinQpsyche.mit.edu. jordan~syche.mit.edu Department of Brain and Cognitive Sciences Massachusetts Institute of Technology Cambridge, MA 02139 Abstract For many types of learners o... | 1994 | 68 |
963 | From Data Distributions to Regularization in Invariant Learning Todd K. Leen Department of Computer Science and Engineering Oregon Graduate Institute of Science and Technology 20000 N.W. Walker Rd Beaverton, Oregon 97006 tieen@cse.ogi.edu Abstract Ideally pattern recognition machines provide ... | 1994 | 69 |
964 | Connectionist Speaker Normalization with Generalized Resource Allocating Networks Cesare Furlanello Istituto per La Ricerca Scientifica e Tecnologica Povo (Trento), Italy furlan«lirst. it Diego Giuliani Istituto per La Ricerca Scientifica e Tecnologica Povo (Trento), Italy giuliani«l... | 1994 | 7 |
965 | An Input Output HMM Architecture Yoshua Bengio* Dept. Informatique et Recherche Operationnelle Universite de Montreal, Qc H3C-3J7 bengioyOIRO.UMontreal.CA Paolo Frasconi Dipartimento di Sistemi e Informatica Universita di Firenze (Italy) paoloOmcculloch.ing.unifi.it Abstract We introduc... | 1994 | 70 |
966 | Grouping Components of Three-Dimensional Moving Objects Area MST of Visual Cortex Richard S. Zemel Carnegie Mellon University Department of Psychology Pittsburgh, PA 15213 zemel«lcmu. edu Terrence J. Sejnowski CNL, The Salk Institute P.O. Box 85800 San Diego, CA 92186-5800 terry«lsal... | 1994 | 71 |
967 | Higher Order Statistical Decorrelation without Information Loss Gustavo Deco SiemensAG Central Research Otto-Hahn-Ring 6 81739 Munich GeIIDany Wilfried Brauer Technische UniversiUit MUnchen Institut fur InfoIIDatik Arcisstr. 21 Abstract 80290 Munich GeIIDany A neural network... | 1994 | 72 |
968 | Sample Size Requirements For Feedforward Neural Networks Michael J. Turmon Cornell U niv. Electrical Engineering Ithaca, NY 14853 mjt@ee.comell.edu Terrence L. Fine Cornell Univ. Electrical Engineering Ithaca, NY 14853 tlfine@ee.comell.edu Abstract We estimate the number of training sam... | 1994 | 73 |
969 | Generalisation in Feedforward Networks Adam Kowalczyk and Herman Ferra Telecom Australia, Research Laboratories 770 Blackburn Road, Clayton, Vic. 3168, Australia (a.kowalczyk@trl.oz.au, h.ferra@trl.oz.au) Abstract We discuss a model of consistent learning with an additional restriction on the probabil... | 1994 | 74 |
970 | The Use of Dynamic Writing Information in a Connectionist On-Line Cursive Handwriting Recognition System Stefan Manke Michael Finke Alex Waibel University of Karlsruhe Computer Science Department D-76128 Karlsruhe, Germany mankeCO)ira. uka.de, finkem@ira.uka.de Carnegie Mellon University ... | 1994 | 75 |
971 |
! #"%$ "'&)(* ,+.-0/ 132546257839!: ; <=>@? A.B!C 2EDGF25= > HIKJLNMOI5PQR!S.TVUWI5X5Y[ZWX]\ H IEJ LN^ I5P_Q R!Sa`bR ^JcdQ IEe3f X]Z I P X I gh ` R ^ Jcdi IEe... | 1994 | 76 |
972 | Capacity and Information Efficiency of a Brain-like Associative Net Bruce Graham and David Willshaw Centre for Cognitive Science, University of Edinburgh 2 Buccleuch Place, Edinburgh, EH8 9LW, UK Email: bruce@cns.ed.ac.uk&david@cns.ed.ac.uk Abstract We have determined the capacity and information e... | 1994 | 77 |
973 | SARDNET: A Self-Organizing Feature Map for Sequences Daniel L. James and Risto Miikkulainen Department of Computer Sciences The University of Texas at Austin Austin, TX 78712 dljames,risto~cs.utexas.edu Abstract A self-organizing neural network for sequence classification called SARDNET is de... | 1994 | 78 |
974 | Deterministic Annealing Variant of the EM Algorithm N aonori U eda Ryohei N alcano ueda@cslab.kecl.ntt.jp nakano@cslab.kecl.ntt.jp NTT Communication Science Laboratories Hikaridai, Seika-cho, Soraku-gun, Kyoto 619-02 Japan Abstract We present a deterministic annealing variant of the EM alg... | 1994 | 79 |
975 | A Novel Reinforcement Model of Birdsong Vocalization Learning Kenji Doya ATR Human Infonnation Processing Research Laboratories 2-2 Hikaridai, Seika, Kyoto 619-02, Japan Abstract Terrence J. Sejnowski Howard Hughes Medical Institute UCSD and Salk Institute, San Diego, CA 92186-5800, USA ... | 1994 | 8 |
976 | A Non-linear Information Maximisation Algorithm that Performs Blind Separation. Anthony J. Bell tonylOsalk.edu Terrence J. Sejnowski terrylOsalk.edu Computational Neurobiology Laboratory The Salk Institute 10010 N. Torrey Pines Road La Jolla, California 92037-1099 and Department of B... | 1994 | 80 |
977 | Real-Time Control of a Tokamak Plasma Using Neural Networks Chris M Bishop Neural Computing Research Group Department of Computer Science Aston University Birmingham, B4 7ET, U.K. c.m.bishop@aston.ac.uk Paul S Haynes, Mike E U Smith, Tom N Todd, David L Trotman and Colin G Windsor AEA Tech... | 1994 | 81 |
978 | Dynamic Cell Structures Jorg Bruske and Gerald Sommer Department of Cognitive Systems Christian Albrechts University at Kiel 24105 Kiel- Germany Abstract Dynamic Cell Structures (DCS) represent a family of artificial neural architectures suited both for unsupervised and supervised learning. They... | 1994 | 82 |
979 | Single Transistor Learning Synapses Paul Hasler, Chris Diorio, Bradley A. Minch, Carver Mead California Institute of Technology Pasadena, CA 91125 (818) 395 - 2812 paul@hobiecat.pcmp.caltech.edu Abstract We describe single-transistor silicon synapses that compute, learn, and provide non-volatile... | 1994 | 83 |
980 | Comparing the prediction accuracy of artificial neural networks and other statistical models for breast cancer survival Harry B. Burke Department of Medicine New York Medical College Valhalla, NY 10595 David B. Rosen Department of Medicine New York Medical College Valhalla, NY 10595 ... | 1994 | 84 |
981 | Learning direction in global motion: two classes of psychophysically-motivated models V. Sundareswaran Lucia M. Vaina* Intelligent Systems Laboratory, College of Engineering, Boston University 44 Cummington Street, Boston, MA 02215 Abstract Perceptual learning is defined as fast improvement i... | 1994 | 85 |
982 | On-line Learning of Dichotomies N. Barkai Racah Institute of Physics The Hebrew University Jerusalem, Israel 91904 naamaCfiz.huji.ac.il H. S. Seung AT&T Bell Laboratories Murray Hill, NJ 07974 seungCphysics.att.com H. Sompolinsky Racah Institute of Physics The Hebrew University Je... | 1994 | 86 |
983 | Asymptotics of Gradient-based Neural Network 'fraining Algorithms Sayandev Mukherjee saymukh~ee.comell.edu School of Electrical Engineering Cornell University Ithaca, NY 14853 Terrence L. Fine tlfine~ee.comell.edu School of Electrical Engineering Cornell University Ithaca, NY 14853 A... | 1994 | 87 |
984 | Convergence Properties of the K-Means Algorithms Leon Bottou Neuristique, 28 rue des Petites Ecuries, 75010 Paris, France leonCneuristique.fr Yoshua Bengio" Dept. LR.O. Universite de Montreal Montreal, Qc H3C-3J7, Canada bengioyCiro.umontreal.ca Abstract This paper studies the con... | 1994 | 88 |
985 | Using Voice Transformations to Create Additional Training Talkers for Word Spotting Eric I. Chang and Richard P. Lippmann MIT Lincoln Laboratory Lexington, MA 02173-0073, USA eichang@sst.ll.mit.edu and rpl@sst.ll.mit.edu Abstract Speech recognizers provide good performance for most users but the ... | 1994 | 89 |
986 | Bias, Variance and the Combination of Least Squares Estimators Ronny Meir Faculty of Electrical Engineering Technion, Haifa 32000 Israel rmeirGee.technion.ac.il Abstract We consider the effect of combining several least squares estimators on the expected performance of a regression problem. C... | 1994 | 9 |
987 | Forward dynamic models in human motor control: Psychophysical evidence Daniel M. Wolpert wolpert@psyche.mit.edu Zouhin Ghahramani zoubin@psyche.mit.edu Michael I. Jordan jordan@psyche.mit.edu Department of Brain & Cognitive Sciences Massachusetts Institute of Technology Cambridge, MA 02139... | 1994 | 90 |
988 | Direction Selectivity In Primary Visual Cortex Using Massive Intracortical Connections Humbert Suarez CNS Program 216-76 Caltech Pasadena, CA 91125 Christof Koch CNS Program 216-76 Caltech Pasadena, CA 91125 Rodney Douglas MRC Anatomical Neuropharmacology Unit University of Oxford... | 1994 | 91 |
989 | Bayesian Query Construction for Neural Network Models Gerhard Paass Jorg Kindermann German National Research Center for Computer Science (GMD) D-53757 Sankt Augustin, Germany paass@gmd.de kindermann@gmd.de Abstract If data collection is costly, there is much to be gained by actively selecting... | 1994 | 92 |
990 | A Silicon Axon Bradley A. Minch, Paul Hasler, Chris Diorio, Carver Mead Physics of Computation Laboratory California Institute of Technology Pasadena, CA 91125 bminch, paul, chris, carver@pcmp.caltech.edu Abstract We present a silicon model of an axon which shows promise as a building block for ... | 1994 | 93 |
991 | Plasticity-Mediated Competitive Learning Nicol N. Schraudolph nici@salk.edu Terrence J. Sejnowski terry@salk.edu Computational Neurobiology Laboratory The Salk Institute for Biological Studies San Diego, CA 92186-5800 and Computer Science & Engineering Department University of California, ... | 1994 | 94 |
992 | Active Learning for Function Approximation Kah Kay Sung (sung@ai.mit.edu) Massachusetts Institute of Technology Artificial Intelligence Laboratory 545 Technology Square Cambridge, MA 02139 Partha Niyogi (pn@ai.mit.edu) Massachusetts Institute of Technology Artificial Intelligence Labora... | 1994 | 95 |
993 | Patterns of damage in neural networks: The effects of lesion area, shape and number Eytan Ruppin and James A. Reggia • Department of Computer Science A.V. Williams Bldg. University of Maryland College Park, MD 20742 ruppin@cs.umd.edu reggia@cs.umd.edu Abstract Current understanding of the ... | 1994 | 96 |
994 | A Study of Parallel Perturbative Gradient Descent D. Lippe· J. Alspector Bellcore Morristown, NJ 07960 Abstract We have continued our study of a parallel perturbative learning method [Alspector et al., 1993] and implications for its implementation in analog VLSI. Our new results indicate that, in m... | 1994 | 97 |
995 | A Neural Model of Delusions and Hallucinations in Schizophrenia Eytan Ruppin and James A. Reggia Department of Computer Science University of Maryland, College Park, MD 20742 ruppin@cs.umd.edu reggia@cs.umd.edu David Horn School of Physics and Astronomy, Tel Aviv University, Tel Aviv 69978, Isra... | 1994 | 98 |
996 | Correlation and Interpolation Networks for Real-time Expression Analysis/Synthesis. Trevor Darrell, Irfan Essa, Alex Pentland Perceptual Computing Group MIT Media Lab Abstract We describe a framework for real-time tracking of facial expressions that uses neurally-inspired correlation and interpolat... | 1994 | 99 |
997 | Learning to Predict Visibility and Invisibility from Occlusion Events Jonathan A. Marshall Richard K. Alley Robert S. Hubbard Department of Computer Science, CB 3175, Sitterson Hall University of North Carolina, Chapel Hill, NC 27599-3175, U.S.A. marshall@cs.unc.edu, 919-962-1887, fax 919-962-17... | 1995 | 1 |
998 | Model Matching and SFMD Computation Steve Rehfuss and Dan Hammerstrom Department of Computer Science and Engineering Oregon Graduate Institute of Science and Technology P.O.Box 91000, Portland, OR 97291-1000 USA stever@cse.ogi.edu, strom@asi.com Abstract In systems that process sensory data ther... | 1995 | 10 |
999 | Using Feedforward Neural Networks to Monitor Alertness from Changes in EEG Correlation and Coherence Scott Makeig Naval Health Research Center, P.O. Box 85122 San Diego, CA 92186-5122 Tzyy-Ping Jung Naval Health Research Center and Computational Neurobiology Lab The Salk Institute, P.O. Box 8... | 1995 | 100 |
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