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 |
|---|---|---|---|
800 | Convergence of Stochastic Iterative Dynamic Programming Algorithms Tommi Jaakkola'" Michael I. Jordan Satinder P. Singh Department of Brain and Cognitive Sciences Massachusetts Institute of Technology Cambridge, MA 02139 Abstract Increasing attention has recently been paid to algorithms based... | 1993 | 48 |
801 | High Performance Neural Net Simulation on a Multiprocessor System with "Intelligent" Communication Urs A. Miiller, Michael Kocheisen, and Anton Gunzinger Electronics Laboratory, Swiss Federal Institute of Technology CH-B092 Zurich, Switzerland Abstract The performance requirements in experimental r... | 1993 | 49 |
802 | The Power of Amnesia Dana Ron Yoram Singer Naftali Tishby Institute of Computer Science and Center for Neural Computation Hebrew University, Jerusalem 91904, Israel Abstract We propose a learning algorithm for a variable memory length Markov process. Human communication, whether given as text... | 1993 | 5 |
803 | An Analog VLSI Model of Central Pattern Generation in the Leech Micah S. Siegel* Department of Electrical Engineering Yale University New Haven, CT 06520 Abstract I detail the design and construction of an analog VLSI model of the neural system responsible for swimming behaviors of the leech. Wh... | 1993 | 50 |
804 | Non-linear Statistical Analysis and Self-Organizing Hebbian Networks Jonathan L. Shapiro and Adam Priigel-Bennett Department of Computer Science The University, Manchester Manchester, UK M139PL Abstract Neurons learning under an unsupervised Hebbian learning rule can perform a nonlinear gener... | 1993 | 51 |
805 | Locally Adaptive Nearest Neighbor Algorithms Dietrich Wettschereck Thomas G. Dietterich Department of Computer Science Oregon State University Corvallis, OR 97331-3202 wettscdGcs.orst.edu Abstract Four versions of a k-nearest neighbor algorithm with locally adaptive k are introduced and compa... | 1993 | 52 |
806 | Bayesian Backprop in Action: Pruning, Committees, Error Bars and an Application to Spectroscopy Hans Henrik Thodberg Danish Meat Research Institute Maglegaardsvej 2, DK-4000 Roskilde thodberg~nn.meatre.dk Abstract MacKay's Bayesian framework for backpropagation is conceptually appealing as we... | 1993 | 53 |
807 | Solvable Models of Artificial Neural Networks Sumio Watanabe Information and Communication R&D Center Ricoh Co., Ltd. 3-2-3, Shin-Yokohama, Kohoku-ku, Yokohama, 222 Japan sumio@ipe.rdc.ricoh.co.jp Abstract Solvable models of nonlinear learning machines are proposed, and learning in artificial... | 1993 | 54 |
808 | A Comparative Study Of A Modified Bumptree Neural Network With Radial Basis Function Networks and the Standard MultiLayer Perceptron. Richard T .J. Bostock and Alan J. Harget Department of Computer Science & Applied Mathematics Aston University Binningham England Abstract Bumptrees are geomet... | 1993 | 55 |
809 | Generalization Error and The Expected Network Complexity Chuanyi Ji Dept. of Elec., Compt. and Syst Engl'. Rensselaer Polytechnic Inst.itu( e Troy, NY 12180-3590 chuanyi@ecse.rpi.edu Abstract For two layer networks with n sigmoidal hidden units, the generalization error is shown to be bounded... | 1993 | 56 |
810 | COMBINED NEURAL NETWORKS FOR TIME SERIES ANALYSIS Iris Ginzburg and David Horn School of Physics and Astronomy Raymond and Beverly Sackler Faculty of Exact Science Tel-Aviv University Tel-A viv 96678, Israel Abstract We propose a method for improving the performance of any network designed to pr... | 1993 | 57 |
811 | Illumination-Invariant Face Recognition with a Contrast Sensitive Silicon Retina Joachim M. Buhmann Rheinische Friedrich-Wilhelms-U niversitiit Institut fUr Informatik II, RomerstraBe 164 0-53117 Bonn, Germany Martin Lades Ruhr-Universitiit Bochum Institut fiir Neuroinformatik 0-44780 Bochum,... | 1993 | 58 |
812 | Address Block Location with a Neural Net System Hans Peter Graf AT&T Bell Laboratories Crawfords Corner Road Holmdel, NJ 07733, USA Abstract Eric Cosatto We developed a system for finding address blocks on mail pieces that can process four images per second. Besides locating the address block, o... | 1993 | 59 |
813 | On the Non-Existence of a Universal Learning Algorithm for Recurrent Neural Networks Herbert Wiklicky Centrum voor Wiskunde en Informatica P.O.Box 4079, NL-1009 AB Amsterdam, The Netherlands· e-mail: herbert@cwi.nl Abstract We prove that the so called "loading problem" for (recurrent) neural networ... | 1993 | 6 |
814 | Assessing the Quality of Learned Local Models Stefan Schaal Christopher G. Atkeson Department of Brain and Cognitive Sciences & The Artifical Intelligence Laboratory Massachusetts Institute of Technology 545 Technology Square, Cambridge, MA 02139 email: sschaal@ai.mit.edu, cga@ai.mit.edu Abstract ... | 1993 | 60 |
815 | Synchronization, oscillations, and 1/ f noise in networks of spiking neurons Martin Stemmler, Marius Usher, and Christof Koch Computation and Neural Systems, 139-74 California Institute of Technology Pasadena, CA 91125 Zeev Olami Dept. of Chemical Physics Weizmann Institute of Science Rehovot... | 1993 | 61 |
816 | What Does the Hippocampus Compute?: A Precis of the 1993 NIPS Workshop Mark A. Gluck Center for Molecular and Behavioral Neuroscience Rutgers University Newark, NJ 07102 gluck@pavlov.rutgers.edu Computational models of the hippocampal-region provide an important method for understanding the func... | 1993 | 62 |
817 | Unsupervised Learning of Mixtures of Multiple Causes in Binary Data Eric Saund Xerox Palo Alto Research Center 3333 Coyote Hill Rd., Palo Alto, CA, 94304 Abstract This paper presents a formulation for unsupervised learning of clusters reflecting multiple causal structure in binary data. Unlike the ... | 1993 | 63 |
818 | A Hodgkin-Huxley Type Neuron Model That Learns Slow Non-Spike Oscillation Kenji Doya* Allen I. Selverston Department of Biology University of California, San Diego La Jolla, CA 92093-0357, USA Abstract Peter F. Rowat A gradient descent algorithm for parameter estimation which is similar to... | 1993 | 64 |
819 | Memory-Based Methods for Regression and Classification Thomas G. Dietterich and Dietrich Wettschereck Department of Computer Science Oregon State University Corvallis, OR 97331-3202 Chris G. Atkeson MIT AI Lab 545 Technology Square Cambridge, MA 02139 Andrew W. Moore School of Computer ... | 1993 | 65 |
820 | Neural Network Methods for Optimization Problems Arun Jagota Department of Mathematical Sciences Memphis State University Memphis, TN 38152 E-mail: jagota~nextl.msci.memst.edu In a talk entitled "Trajectory Control of Convergent Networks with applications to TSP", Natan Peterfreund (Computer ... | 1993 | 66 |
821 | A Comparison of Dynamic Reposing and Tangent Distance for Drug Activity Prediction Thomas G. Dietterich Arris Pharmaceutical Corporation and Oregon State University Corvallis, OR 97331-3202 Ajay N. Jain Arris Pharmaceutical Corporation 385 Oyster Point Blvd., Suite 3 South San Francisco, CA 9... | 1993 | 67 |
822 | Hoo Optimality Criteria for LMS and Backpropagation Babak Hassibi Information Systems Laboratory Stanford University Stanford, CA 94305 Ali H. Sayed Dept. of Elec. and Compo Engr. University of California Santa Barbara Santa Barbara, CA 93106 Thomas Kailath Information Systems Laborator... | 1993 | 68 |
823 | Classifying Hand Gestures with a View-based Distributed Representation Trevor J. Darrell Perceptual Computing Group MIT Media Lab Abstract Alex P. Pentland Perceptual Computing Group MIT Media Lab We present a method for learning, tracking, and recognizing human hand gestures recorded by a... | 1993 | 69 |
824 | Constructive Learning Using Internal Representation Conflicts Laurens R. Leerink and Marwan A. J abri Systems Engineering & Design Automation Laboratory Department of Electrical Engineering The University of Sydney Sydney, NSW 2006, Australia Abstract We present an algorithm for the training of ... | 1993 | 7 |
825 | Optimal Unsupervised Motor Learning Predicts the Internal Representation of Barn Owl Head Movements Terence D. Sanger Jet Propulsion Laboratory MS 303-310 4800 Oak Grove Drive Pasadena, CA 91109 Abstract (Masino and Knudsen 1990) showed some remarkable results which suggest that head motio... | 1993 | 70 |
826 | Amplifying and Linearizing Apical Synaptic Inputs to Cortical Pyramidal Cells. Ojvind Bernander, Christof Koch ... Computation and Neural Systems Program, California Institute of Technology, 139-74 Pasadena, Ca 91125, USA. Rodney J. Douglas Anatomical Neuropharmacology Unit, Dept. Pharmacolog... | 1993 | 71 |
827 | Decoding Cursive Scripts Yoram Singer and Naftali Tishby Institute of Computer Science and Center for Neural Computation Hebrew University, Jerusalem 91904, Israel Abstract Online cursive handwriting recognition is currently one of the most intriguing challenges in pattern recognition. This s... | 1993 | 72 |
828 | Foraging in an Uncertain Environment Using Predictive Hebbian Learning P. Read Montague: Peter Dayan, and Terrence J. Sejnowski Computational Neurobiology Lab, The Salk Institute, 100 ION. Torrey Pines Rd, La Jolla, CA, 92037, USA read~bohr.bcm.tmc.edu Abstract Survival is enhanced by an ability... | 1993 | 73 |
829 | Analysis of Short Term Memories for Neural Networks Jose C. Principe, Hui-H. Hsu and Jyh-Ming Kuo Computational NeuroEngineering Laboratory Department of Electrical Engineering University of Florida, CSE 447 Gainesville, FL 32611 principe@synapse.ee.ufi.edu Abstract Short term memory is indis... | 1993 | 74 |
830 | Credit Assignment through Time: Alternatives to Backpropagation Yoshua Bengio * Dept. Informatique et Recherche Operationnelle Universite de Montreal Montreal, Qc H3C-3J7 Paolo Frasconi Dip. di Sistemi e Informatica Universita di Firenze 50139 Firenze (Italy) Abstract Learning to rec... | 1993 | 75 |
831 | Analyzing Cross Connected Networks and Jeffrey L. Elman Thomas R. Shultz Department of Psychology & McGill Cognitive Science Centre McGill University Montreal, Quebec, Canada H3A IB 1 shultz@psych.mcgill.ca Center for Research on Language Department of Cognitive Science University of Ca... | 1993 | 76 |
832 | Recognition-based Segmentation of On-line Cursive Handwriting Nicholas S. Flann Department of Computer Science Utah State University Logan, UT 84322-4205 flannGnick.cs.usu.edu Abstract This paper introduces a new recognition-based segmentation approach to recognizing on-line cursive handwriting ... | 1993 | 77 |
833 | Implementing Intelligence on Silicon Using Neuron-Like Functional MOS Transistors Tadashi Shibatat Koji Kotani t Takeo Yamashitat Hiroshi Ishii Hideo Kosakat and Tadahiro Ohmi Department of Electronic Engineering Tohoku University Aza-Aoba, Aramaki, Aobaku, Sendai 980 lAP AN Abstract We will pre... | 1993 | 78 |
834 | Probabilistic Anomaly Detection Dynamic Systems Padhraic Smyth Jet Propulsion Laboratory 238-420 California Institute of Technology 4800 Oak Grove Drive Pasadena, CA 91109 Abstract • In This paper describes probabilistic methods for novelty detection when using pattern recognition methods ... | 1993 | 79 |
835 | A Local Algorithm to Learn Trajectories with Stochastic Neural Networks Javier R. Movellan· Department of Cognitive Science University of California San Diego La Jolla, CA 92093-0515 Abstract This paper presents a simple algorithm to learn trajectories with a continuous time, continuous activati... | 1993 | 8 |
836 | Learning Complex Boolean Functions: Algorithms and Applications Arlindo L. Oliveira and Alberto Sangiovanni-Vincentelli Dept. of EECS UC Berkeley Berkeley CA 94720 Abstract The most commonly used neural network models are not well suited to direct digital implementations because each node needs ... | 1993 | 80 |
837 | A Unified Gradient-Descent/Clustering Architecture for Finite State Machine Induction Sreerupa Das and Michael C. Mozer Department of Computer Science University of Colorado Boulder, CO 80309-0430 Abstract Although recurrent neural nets have been moderately successful in learning to emulate f... | 1993 | 81 |
838 | Convergence of Indirect Adaptive Asynchronous Value Iteration Algorithms Vijaykumar Gullapalli Department of Computer Science University of Massachusetts Amherst, MA 01003 vijay@cs.umass.edu Andrew G. Barto Department of Computer Science University of Massachusetts Amherst, MA 01003 bar... | 1993 | 82 |
839 | Fast Pruning Using Principal Components Asriel U. Levin, Todd K. Leen and John E. Moody Department of Computer Science and Engineering Oregon Graduate Institute P.O. Box 91000 Portland, OR 97291-1000 Abstract We present a new algorithm for eliminating excess parameters and improving network g... | 1993 | 83 |
840 | Hidden Markov Models for Human Genes Pierre Baldi * Jet Propulsion Laboratory California Institute of Technology Pasadena, CA 91109 Yves Chauvin t Net-ID, Inc. 601 Minnesota San Francisco, CA 94107 S0ren Brunak Center for Biological Sequence Analysis The Technical University of Denma... | 1993 | 84 |
841 | Postal Address Block Location Using A Convolutional Locator Network Ralph Wolf and John C. Platt Synaptics, Inc. 2698 Orchard Parkway San Jose, CA 95134 Abstract This paper describes the use of a convolutional neural network to perform address block location on machine-printed mail pieces. Lo... | 1993 | 85 |
842 | An Analog VLSI Saccadic Eye Movement System Timothy K. Horiuchi Brooks Bishofberger and Christof Koch Computation and Neural Systems Program California Institute of Technology MS 139-74 Pasadena, CA 91125 Abstract In an effort to understand saccadic eye movements and their relation to visu... | 1993 | 86 |
843 | An Optimization Method of Layered Neural Networks based on the Modified Information Criterion Sumio Watanabe Information and Communication R&D Center Ricoh Co., Ltd. 3-2-3, Shin-Yokohama, Kohoku-ku, Yokohama, 222 Japan sumio@ipe.rdc.ricoh.co.jp Abstract This paper proposes a practical optimiz... | 1993 | 87 |
844 | A Computational Model for Cursive Handwriting Based on the Minimization Principle Yasuhiro Wada * Yasuharu Koike Eric Vatikiotis-Bateson Mitsuo Kawato A TR Human Infonnation Processing Research Laboratories 2-2 Hikaridai, Seika-cho, Soraku-gun, Kyoto 619-02, Japan ABSTRACT We propose a tra... | 1993 | 88 |
845 | Discontinuous Generalization in Large Committee Machines H. Schwarze Dept. of Theoretical Physics Lund University Solvegatan 14A 223 62 Lund Sweden Abstract J. Hertz Nordita Blegdamsvej 17 2100 Copenhagen 0 Denmark The problem of learning from examples in multilayer networks is... | 1993 | 89 |
846 | Use of Bad Training Data For Better Predictions Tal Grossman Complex Systems Group (T13) and CNLS LANL, MS B213 Los Alamos N .M. 87545 Alan Lapedes Complex Systems Group (T13) LANL, MS B213 Los Alamos N.M. 87545 and The Santa Fe Institute, Santa Fe, New Mexico Abstract We show how randomly... | 1993 | 9 |
847 | Inverse Dynamics of Speech Motor Control Makoto Hirayama Eric Vatikiotis-Datesol1 Mitsuo Kawato" ATR Human Information Processing Research Laboratories 2-2 Hikaridai, Seika-cho, Soraku-gun, Kyoto 619-02, Japan Abstract Progress ha.s been made in comput.ational implementation of speech product... | 1993 | 90 |
848 | Learning Temporal Dependencies in Connectionist Speech Recognition Steve Renals Mike Hocbberg Tony Robinson Cambridge University Engineering Department Cambridge CB2 IPZ, UK {sjr,mmh,ajr}@eng.cam.ac.uk Abstract Hybrid connectionistfHMM systems model time both using a Markov chain and throu... | 1993 | 91 |
849 | Odor Processing in the Bee: a Preliminary Study of the Role of Central Input to the Antennal Lobe. Christiane Linster David Marsan ESPeI, Laboratoire d'Electronique 10, Rue Vauquelin, 75005 Paris linster@neurones.espci.fr Claudine Masson Laboratoire de Neurobiologie Comparee des Invertebre... | 1993 | 92 |
850 | Surface Learning with Applications to Lipreading Christoph Bregler *.** *Computer Science Division University of California Berkeley, CA 94720 Stephen M. Omohundro ** **Int. Computer Science Institute 1947 Center Street Suite 600 Berkeley, CA 94704 Abstract Most connectionist research h... | 1993 | 93 |
851 | Figure of Merit Training for Detection and Spotting Eric I. Chang and Richard P. Lippmann MIT Lincoln Laboratory Lexington, MA 02173-0073, USA Abstract Spotting tasks require detection of target patterns from a background of richly varied non-target inputs. The performance measure of interest for ... | 1993 | 94 |
852 |
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853 | Autoencoders, Minimum Description Length and Helmholtz Free Energy Geoffrey E. Hinton Department of Computer Science University of Toronto 6 King's College Road Toronto M5S lA4, Canada Richard S. Zemel Computational Neuroscience Laboratory The Salk Institute 10010 North Torrey Pines Road ... | 1993 | 96 |
854 | Dual Mechanisms for Neural Binding and Segmentation Paul Sajda and Leif H. Finkel Department of Bioengineering and Institute of Neurological Science University of Pennsylvania 220 South 33rd Street Philadelphia, PA. 19104-6392 Abstract We propose that the binding and segmentation of visual fe... | 1993 | 97 |
855 | The Statistical Mechanics of k-Satisfaction Scott Kirkpatrick* Racah Institute for Physics and Center for Neural Computation Hebrew University Jerusalem, 91904 Israel kirk@fiz.huji.ac.il Geza Gyorgyi Institute for Theoretical Physics Eotvos University 1-1088 Puskin u. 5-7 Budapest, H... | 1993 | 98 |
856 | Lipreading by neural networks: Visual preprocessing, learning and sensory integration Gregory J. Wolff Ricoh California Research Center 2882 Sand Hill Road Suite 115 Menlo Park, CA 94025-7022 wolff@crc.ricoh.com K. Venkatesh Prasad Ricoh California Research Center 2882 Sand Hill Road Suite... | 1993 | 99 |
857 | SIMPLIFYING NEURAL NETS BY DISCOVERING FLAT MINIMA Sepp Hochreiter" Jiirgen Schmidhubert Fakultat fiir Informatik, H2 Technische Universitat Miinchen 80290 Miinchen, Germany Abstract We present a new algorithm for finding low complexity networks with high generalization capability. The algori... | 1994 | 1 |
858 | Hierarchical Mixtures of Experts Methodology Applied to Continuous Speech Recognition Ying Zhao, Richard Schwartz, Jason Sroka*: John Makhoul BBN System and Technologies 70 Fawcett Street Cambridge MA 02138 Abstract In this paper, we incorporate the Hierarchical Mixtures of Experts (HME) method ... | 1994 | 10 |
859 | Neural Network Ensembles, Cross Validation, and Active Learning Anders Krogh" Nordita Blegdamsvej 17 2100 Copenhagen, Denmark Jesper Vedelsby Electronics Institute, Building 349 Technical University of Denmark 2800 Lyngby, Denmark Abstract Learning of continuous valued functions using n... | 1994 | 100 |
860 | Extracting Rules from Artificial Neural Networks with Distributed Representations Sebastian Thrun University of Bonn Department of Computer Science III Romerstr. 164, D-53117 Bonn, Germany E-mail: thrun@carbon.informatik.uni-bonn.de Abstract Although artificial neural networks have been applied ... | 1994 | 101 |
861 | A model of the hippocampus combining selforganization and associative memory function. Michael E. Hasselmo, Eric Schnell Joshua Berke and Edi Barkai Dept. of Psychology, Harvard University 33 Kirkland St., Cambridge, MA 02138 hasselmo@katla.harvard.edu Abstract A model of the hippocampus is present... | 1994 | 102 |
862 | Glove-TalkII: Mapping Hand Gestures to Speech Using Neural Networks S. Sidney Fels Department of Computer Science University of Toronto Toronto, ON, M5S lA4 ssfels@ai.toronto.edu Geoffrey Hinton Department of Computer Science University of Toronto Toronto, ON, M5S lA4 hinton@ai.toronto.... | 1994 | 103 |
863 | Learning in large linear perceptrons and why the thermodynamic limit is relevant to the real world Peter Sollich Department of Physics, University of Edinburgh Edinburgh EH9 3JZ, U.K. P.Sollich~ed.ac.uk Abstract We present a new method for obtaining the response function 9 and its average G f... | 1994 | 104 |
864 | Learning Saccadic Eye Movements Using Multiscale Spatial Filters Rajesh P.N. Rao and Dana H. Ballard Department of Computer Science University of Rochester Rochester, NY 14627 {rao)dana}~cs.rochester.edu Abstract We describe a framework for learning saccadic eye movements using a photometric ... | 1994 | 105 |
865 | A Charge-Based CMOS Parallel Analog Vector Quantizer Gert Cauwenberghs Johns Hopkins University ECE Department 3400 N. Charles St. Baltimore, MD 21218-2686 gert@jhunix.hcf.jhu.edu Volnei Pedroni California Institute of Technology EE Department Mail Code 128-95 Pasadena, CA 91125 p... | 1994 | 106 |
866 | Boosting the Performance of RBF Networks with Dynamic Decay Adjustment Jay Diamond Intel Corporation 2200 Mission College Blvd. Santa Clara, CA, USA 95052 MS:SC9-15 Michael R. Berthold Forschungszentrum Informatik Gruppe ACID (Prof. D. Schmid) Haid-und-Neu-Strasse 10-14 76131 Karlsru... | 1994 | 107 |
867 | An Alternative Model for Mixtures of Experts Lei Xu Dept. of Computer Science, The Chinese University of Hong Kong Shatin, Hong Kong, Emaillxu@cs.cuhk.hk Michael I. Jordan Dept. of Brain and Cognitive Sciences MIT Cambridge, MA 02139 Abstract Geoffrey E. Hinton Dept. of Computer Science... | 1994 | 108 |
868 | Catastrophic Interference in Human Motor Learning Tom Brashers-Krug, Reza Shadmehrt, and Emanuel Todorov Dept. of Brain and Cognitive Sciences, M. I. T., Cambridge, MA 02139 tCurrently at Dept. of Biomedical Eng., Johns Hopkins Univ., Baltimore, MD 21205 Email: tbk@ai.mit.edu, reza@bme.jhu.edu, emo@aLmit... | 1994 | 109 |
869 | A Comparison of Discrete-Time Operator Models for Nonlinear System Identification Andrew D. Back, Ah Chung Tsoi Department of Electrical and Computer Engineering, University of Queensland St. Lucia, Qld 4072. Australia. e-mail: {back.act}@elec.uq.oz.au Abstract We present a unifying view of disc... | 1994 | 11 |
870 | On the Computational Complexity of Networks of Spiking Neurons (Extended Abstract) Wolfgang Maass Institute for Theoretical Computer Science Technische Universitaet Graz A-80lO Graz, Austria e-mail: maass@igi.tu-graz.ac.at Abstract We investigate the computational power of a formal model for ... | 1994 | 110 |
871 | New Algorithms for 2D and 3D Point Matching: Pose Estimation and Correspondence Steven Goldl , Chien Ping LuI, Anand Rangarajanl , Suguna Pappul and Eric Mjolsness2 Department of Computer Science Yale University New Haven, CT 06520-8285 Abstract A fundamental open problem in computer vision-d... | 1994 | 111 |
872 | PCA-Pyramids for Image Compression* Horst Bischof Department for Pattern Recognition and Image Processing Technical University Vienna Treitlstraf3e 3/1832 A-1040 Vienna, Austria bis@prip.tuwien.ac.at Kurt Hornik Institut fur Statistik und Wahrscheinlichkeitstheorie Technische UniversiUi... | 1994 | 112 |
873 | Morphogenesis of the Lateral Geniculate Nucleus: How Singularities Affect Global Structure Svilen Tzonev Beckman Institute University of Illinois Urbana, IL 61801 svilen@ks.uiuc.edu Klaus Schulten Beckman Institute University of Illinois Urbana, IL 61801 kschulte@ks.uiuc.edu Josep... | 1994 | 113 |
874 | 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 | 114 |
875 | A Lagrangian Formulation For Optical Backpropagation Training In Kerr-Type Optical Networks James E. Steck Mechanical Engineering Wichita State University Wichita, KS 67260-0035 Alvaro A. Cruz-Cabrara Electrical Engineering Wichita State University Wichita, KS 67260-0044 Abstract Ste... | 1994 | 115 |
876 | Instance-Based State Identification for Reinforcement Learning R. Andrew McCallum Department of Computer Science University of Rochester Rochester, NY 14627-0226 mccallumCcs.rochester.edu Abstract This paper presents instance-based state identification, an approach to reinforcement learning a... | 1994 | 116 |
877 | Nonlinear Image Interpolation using Manifold Learning Christoph Bregler Computer Science Division University of California Berkeley, CA 94720 bregler@cs.berkeley.edu Stephen M. Omohundro'" Int. Computer Science Institute 1947 Center Street Suite 600 Berkeley, CA 94704 om@research.nj .ne... | 1994 | 117 |
878 | A Growing Neural Gas Network Learns Topologies Bernd Fritzke Institut fur Neuroinformatik Ruhr-Universitat Bochum D-44 780 Bochum Germany Abstract An incremental network model is introduced which is able to learn the important topological relations in a given set of input vectors by means ... | 1994 | 118 |
879 | Transformation Invariant Autoassociation with Application to Handwritten Character Recognition Holger Schwenk Maurice Milgram PARC Universite Pierre et Marie Curie tour 66-56, boite 164 4, place Jussieu, 75252 Paris cedex 05, France. e-mail: schwenk@robo.jussieu.fr Abstract When trainin... | 1994 | 119 |
880 | Learning Many Related Tasks at the Same Time With Backpropagation Rich Caruana School of Computer Science Carnegie Mellon University Pittsburgh, PA 15213 caruana@cs.cmu.edu Abstract Hinton [6] proposed that generalization in artificial neural nets should improve if nets learn to represent the... | 1994 | 12 |
881 | Learning To Play the Game of Chess Sebastian Thrun University of Bonn Department of Computer Science III Romerstr. 164, 0-53117 Bonn, Germany E-mail: thrun@carbon.informatik.uni-bonn.de Abstract This paper presents NeuroChess, a program which learns to play chess from the final outcome of games.... | 1994 | 120 |
882 | Interior Point Implementations of Alternating Minimization Training Michael Lemmon Dept. of Electrical Engineering University of Notre Dame Notre Dame, IN 46556 lemmon@maddog.ee.nd.edu Peter T. Szymanski Dept. of Electrical Engineering University of Notre Dame Notre Dame, IN 46556 pszym... | 1994 | 121 |
883 | A Convolutional Neural Network Hand Tracker Steven J. Nowlan Synaptics, Inc. 2698 Orchard Parkway San Jose, CA 95134 nowlan@synaptics.com Abstract John C. Platt Synaptics, Inc. 2698 Orchard Parkway San Jose, CA 95134 platt@synaptics.com We describe a system that can track a hand i... | 1994 | 122 |
884 | Temporal Dynamics of Generalization Neural Networks • In Changfeng Wang Department of Systems Engineering University Of Pennsylvania Philadelphia, PA 19104 fwang~ender.ee.upenn.edu Santosh S. Venkatesh Department of Electrical Engineering University Of Pennsylvania Philadelphia, PA 1910... | 1994 | 123 |
885 | Learning Stochastic Perceptrons Under k-Blocking Distributions Mario Marchand Ottawa-Carleton Institute for Physics University of Ottawa Ottawa, Ont., Canada KIN 6N5 mario@physics.uottawa.ca Saeed Hadjifaradji Ottawa-Carleton Institute for Physics University of Ottawa Ottawa, Ont., Canada ... | 1994 | 124 |
886 | Recurrent Networks: Second Order Properties and Pruning Morten With Pedersen and Lars Kai Hansen CONNECT, Electronics Institute Technical University of Denmark B349 DK-2800 Lyngby, DENMARK emails:with.lkhansen@ei.dtu.dk Abstract Second order properties of cost functions for recurrent networks ... | 1994 | 125 |
887 | Unsupervised Classification of 3D Objects from 2D Views Satoshi Suzuki Hiroshi Ando A TR Human Information Processing Research Laboratories 2-2 Hikaridai, Seika-cho, Soraku-gun, Kyoto 619-02, Japan satoshi@hip.atr.co.jp, ando@hip.atr.co.jp Abstract This paper presents an unsupervised learning sc... | 1994 | 126 |
888 | Hyperparameters, Evidence and Generalisation for an Unrealisable Rule Glenn Marion and David Saad glennyGed.ac.uk, D.SaadGed.ac.uk Department of Physics, University of Edinburgh, Edinburgh, EH9 3JZ, U.K. Abstract Using a statistical mechanical formalism we calculate the evidence, generalisation ... | 1994 | 127 |
889 | Adaptive Elastic Input Field for Recognition Improvement Minoru Asogawa C&C Research Laboratories, NEe Miyamae, Miyazaki, Kawasaki Kanagawa 213 Japan asogawa~csl.cl.nec.co.jp Abstract For machines to perform classification tasks, such as speech and character recognition, appropriately handling d... | 1994 | 128 |
890 | A Model for Chemosensory Reception Rainer MalakaJ Thomas Ragg Institut fUr Logik, Komplexitat und Oeduktionssysteme Universitat Karlsruhe, PO Box 0-76128 Karlsruhe, Germany e-mail: malaka@ira.uka.de.ragg@ira.uka.de Martin Hammer Institut fur Neurobiologie Freie Universitat Berlin 0-14195 Berl... | 1994 | 129 |
891 | Multidimensional Scaling and Data Clustering Thomas Hofmann & Joachim Buhmann Rheinische Friedrich-Wilhelms-U niversitat Institut fur Informatik ill, Romerstra6e 164 D-53117 Bonn, Germany email:{th.jb}@cs.uni-bonn.de Abstract Visualizing and structuring pairwise dissimilarity data are difficult com... | 1994 | 13 |
892 | A Real Time Clustering CMOS Neural Engine T. Serrano-Gotarredona, B. Linares-Barranco, and J. L. Huertas Dept. of Analog Design, National Microelectronics Center (CNM), Ed. CICA, Av. Reina Mercedes sIn, 41012 Sevilla, SPAIN. Phone: (34)-5-4239923, Fax: (34)-5-4624506, E-mail: bernabe@cnm.us.es Abstrac... | 1994 | 130 |
893 | Learning from queries for maximum information gain in imperfectly learnable problems Peter Sollich David Saad Department of Physics, University of Edinburgh Edinburgh EH9 3JZ, U.K. P.Sollich~ed.ac.uk. D.Saad~ed.ac.uk Abstract In supervised learning, learning from queries rather than from rand... | 1994 | 131 |
894 | Factorial Learning by Clustering Features Joshua B. Tenenbaum and Emanuel V. Todorov Department of Brain and Cognitive Sciences Massachusetts Institute of Technology Cambridge, MA 02139 {jbt.emo}~psyche . mit.edu Abstract We introduce a novel algorithm for factorial learning, motivated by segmen... | 1994 | 132 |
895 | Generalization in Reinforcement Learning: Safely Approximating the Value Function Justin A. Boyan and Andrew W. Moore Computer Science Department Carnegie Mellon University Pittsburgh, PA 15213 jab@cs.cmu.edu, awm@cs.cmu.edu Abstract A straightforward approach to the curse of dimensionality in r... | 1994 | 133 |
896 | A Rapid Graph-based Method for Arbitrary Transformation-Invariant Pattern Classification Alessandro Sperduti Dipartimento di Informatica U niversita di Pisa Corso Italia 40 56125 Pisa, ITALY perso~di.unipi.it David G. Stork Machine Learning and Perception Group Ricoh California Research... | 1994 | 134 |
897 | A solvable connectionist model of immediate recall of ordered lists Neil Burgess Department of Anatomy, University College London London WC1E 6BT, England (e-mail: n.burgessOucl.ac.uk) Abstract A model of short-term memory for serially ordered lists of verbal stimuli is proposed as an implementa... | 1994 | 135 |
898 |
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899 | U sing a neural net to instantiate a deformable model Christopher K. I. Williams; Michael D. Revowand Geoffrey E. Hinton Department of Computer Science, University of Toronto Toronto, Ontario, Canada M5S lA4 Abstract Deformable models are an attractive approach to recognizing nonrigid objects which ha... | 1994 | 137 |
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