Self-Organizing Maps of Massive Document Collections

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Session TB1: Statistical Frameworks for Learning

Stochastic Resonance Neural Network and Its Performance (Abstract)

Tatsuhiko Nobori, Himeji Institute of Technology

Nobuyuki Matsui, Himeji Institute of Technology

pp. 2013

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Bayesian Field Theory: Nonparametric Approaches to Density Estimation (Abstract)

Jörg C. Lemm, Universit?t M?nster

pp. 2018

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Large Margin Classifier via Semiparametric Inference (Abstract)

Koji Tsuda, Electrotechnical Laboratory

Shotaro Akaho, Electrotechnical Laboratory

pp. 2023

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Parallel Non Linear Dichotomizers (Abstract)

Francesco Masulli, Universit? di Genova

Giorgio Valentini, Universit? di Genova

pp. 2029

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Session TB2: Neurocognition I

Pattern Recognition with Eye Movement: A Neural Network Model (Abstract)

Masayuki Kikuchi, University of Tsukuba

Kunihiko Fukushima, University of Electro-Communications,

pp. 2037

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A Hippocampal Model of Visually Guided Navigation as Implemented by a Mobile Agent (Abstract)

Jean P. Banquet, INSERM

Yves Burnod, INSERM

Philippe Gaussier, Universit? de Cergy-Pontoise/ENSEA

Arnaud Revel, Universit? de Cergy-Pontoise/ENSEA

pp. 2041

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Session TB3: Hardware Implementation I

A Full-Parallel Digital Implementation for Pre-Trained NNs (Abstract)

Tamás Szabó, Technical University of Budapest

Lörinc Antoni, Technical University of Budapest

Gábor Horváth, Technical University of Budapest

Béla Fehér, Technical University of Budapest

pp. 2049

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FPGA Architecture Comparison for Non-Conventional Signal Processing (Abstract)

D. Franco, Universidade Federal do Rio Grande do Sul

L. Carro, Universidade Federal do Rio Grande do Sul

pp. 2055

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Building a 2D-Compatible Multilayer Neural Network (Abstract)

Bernard Girau, McGill University

pp. 2059

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Hardware Implementation of a PCA Learning Network by an Asynchronous PDM Digital Circuit (Abstract)

Yuzo Hirai, University of Tsukuba

Kuninori Nishizawa, University of Tsukuba

pp. 2065

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Pulse Mode Multilayer Neural Network with Floating Point Operation and On-Chip Learning (Abstract)

Hiroomi Hikawa, Oita University

pp. 2071

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Session TB6: Special Session on 'From Subsymbolic Neural Network Representations to Symbols'

A Theory of the Brain: There Are Parts of the Brain That Control Other Parts (Abstract)

Asim Roy, Arizona State University

pp. 2081

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A General Framework for Symbol and Rule Extraction in Neural Networks (Abstract)

B. Apolloni, University of Milan

C. Orovas, University of Milan

J. Taylor, King's College London

W. Fellenz, King's College London

Stan Gielen, University of Nijmegen

Machiel Westerdijk, University of Nijmegen

pp. 2087

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On Emotion Recognition of Faces and of Speech Using Neural Networks, Fuzzy Logic and the ASSESS System (Abstract)

W.A. Fellenz, King's College

J.G. Taylor, King's College

R. Cowie, Queen's University of Belfast

E. Douglas-Cowie, Queen's University of Belfast

F. Piat, National Technical University of Athens

S. Kollias, National Technical University of Athens

C. Orovas, University of Milan

B. Apolloni, University of Milan

pp. 2093

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Constructing Symbols as Manipulable Structures by Recurrent Networks (Abstract)

J.G. Taylor, King's College London

N.R. Taylor, King's College London

B Apolloni, University of Milan

C Orovas, University of Milan

pp. 2099

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Beyond Simple Rule Extraction: The Extraction of Planning Knowledge from Reinforcement Learners (Abstract)

Ron Sun, University of Missouri at Columbia

pp. 2105

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Session TB7: Multilayer Perceptrons III

The Inefficiency of Batch Training for Large Training Sets (Abstract)

D. Randall Wilson, fonix Corporation

Tony R. Martinez, Brigham Young University

pp. 2113

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Tree-Structured Neural Networks: Efficient Evaluation of Higher-Order Derivatives and Integrals (Abstract)

Alois P. Heinz, Universit?t Freiburg

pp. 2118

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Backpropagation Algorithm for Logic Oriented Neural Networks (Abstract)

Takeshi Kamio, Hiroshima City University

Shinichiro Tanaka, Hiroshima City University

Mititada Morisue, Hiroshima City University

pp. 2123

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A Hyperbolic Multilayer Perceptron (Abstract)

Sven Buchholz, University of Kiel

Gerald Sommer, University of Kiel

pp. 2129

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Session TB8: Pattern Recognition I

Spreading Associative Neural Network Recognizes the Shape and Position of an Object Simultaneously (Abstract)

Kiyomi Nakamura, Toyama Prefectural University

Noriki Kinoshita, Toyama Prefectural University

Hirokazu Kanayama, Toyama Prefectural University

Takashi Minami, Toyama Prefectural University

pp. 2137

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Multiple Kinds of Paper Currency Recognition Using Neural Network and Application for Euro Currency (Abstract)

Fumiaki Takeda, Kochi University of Technology

Toshihiro Nishikage, GLORY LTD.

pp. 2143

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A Neural Network Approach to Hyphenating Norwegian (Abstract)

Terje Kristensen, Bergen University College

pp. 2148

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Improved Rotational Invariance for Statistical Inverse in Electrical Impedance Tomography (Abstract)

Jani Lahtinen, Helsinki University of Technology

Tomas Martinsen, Helsinki University of Technology

Jouko Lampinen, Helsinki University of Technology

pp. 2154

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Pattern Matching in High Energy Physics by Using Neural Network and Genetic Algorithm (Abstract)

Marcello Castellano, Politecnico di Bari

Giuseppe Mastronardi, Politecnico di Bari

Vitoantonio Bevilacqua, Politecnico di Bari

E. Nappi, INFN sezione di Bari

pp. 2159

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Session TD4: Plenary Talk

Searching the Web: Fundamental Limitations, Artificial Intelligence, and Future Directions

Session TE1: Supervised Learning III

On Derivation of MLP Backpropagation from the Kelley-Bryson Optimal-Control Gradient Formula and Its Application (Abstract)

Eiji Mizutani, University of California at Berkeley and Sony US Research Laboratories

Stuart E. Dreyfus, University of California at Berkeley

Kenichi Nishio, Sony Corporation Personal IT Network Company

pp. 2167

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Training Feedforward Neural Networks Using Orthogonal Iteration of the Hessian Eigenvectors (Abstract)

Andrew Hunter, University of Sunderland

pp. 2173

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Effective Learning in Noisy Environment Using Neural Network Ensemble (Abstract)

Pitoyo Hartono, Waseda University

Shuji Hashimoto, Waseda University

pp. 2179

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Evaluation of Gradient Descent Learning Algorithms with an Adaptive Local Rate Technique for Hierarchical Feed Forward Architectures (Abstract)

F. Diotalevi, University of Genova

M. Valle, University of Genova

D.D. Caviglia, University of Genova

pp. 2185

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Analyzing Learning Dynamics: How to Average? (Abstract)

Christian Goerick, Ruhr-Universit?t Bochum

pp. 2191

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Session TE2: Neurocognition II

Unfaithful Population Decoding (Abstract)

Si Wu, RIKEN Brain Science Institute

Danmei Chen, RIKEN Brain Science Institute

Shun-ichi Amari, RIKEN Brain Science Institute

pp. 2199

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The Hidden Layer Associative Memory Model of Hippocampus (Abstract)

Winfried A. Fellenz, King's College

John G. Taylor, King's College

pp. 2205

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Frequency-Based Error Back-Propagation in a Cortical Network (Abstract)

Rafal Bogacz, University of Bristol

Malcolm W. Brown, University of Bristol

Christophe Giraud-Carrier, University of Bristol

pp. 2211

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Is There More to TSSG than Associative Chaining (Chunking and All That)? (Abstract)

N.R. Taylor, King's College

J.G. Taylor, King's College

pp. 2217

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Session TE3: Time Series Prediction I

Time Series Prediction by a Neural Network Model Based on the Bi-Directional Computation Style (Abstract)

Hiroshi Wakuya, University of Louisville

Jacek M. Zurada, University of Louisville

pp. 2225

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Predicting Chaotic Time Series by Ensemble Self-Generating Neural Networks (Abstract)

Hirotaka Inoue, Okayama University of Science

Hiroyuki Narihisa, Okayama University of Science

pp. 2231

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Input Window Size and Neural Network Predictors (Abstract)

R.J. Frank, University of Hertfordshire

N. Davey, University of Hertfordshire

S.P. Hunt, University of Hertfordshire

pp. 2237

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On the Use of Neural Networks in the Generalized Likelihood Ratio Test for Detecting Abrupt Changes in Signals (Abstract)

Craig L. Fancourt, University of Florida at Gainesville

Jose C. Principe, University of Florida at Gainesville

pp. 2243

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Session TE6: Symbolic and Sub-Symbolic Computation I

Complex Preferences for the Integration of Neural Codes (Abstract)

Christo Panchev, University of Sunderland

Stefan Wermter, University of Sunderland

pp. 2253

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Extracting Distributed Representations of Concepts and Relations from Positive and Negative Propositions (Abstract)

Alberto Paccanaro, University College London

Geoffrey E. Hinton, University College London

pp. 2259

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Building Predictive Models on Complex Symbolic Sequences with a Second-Order Recurrent BCM Network with Lateral Inhibition (Abstract)

Peter Tino, Slovak Technical University

Michal Stancík, Slovak Technical University

Lubica Benu?ková, Slovak Technical University

pp. 2265

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Refining Hidden Markov Models with Recurrent Neural Networks (Abstract)

T. Wessels, University of Stellenbosch

C.W. Omlin, University of Stellenbosch

pp. 2271

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Session TE8: Pattern Recognition II

A Comparison of Feature Sets and Neural Network Classifiers on a Bird Removal Approach for Wind Profiler Data (Abstract)

Ralf Kretzschmar, Swiss Federal Institute of Technology

Hans Richner, Swiss Federal Institute of Technology

Nicolaos B. Karayiannis, University of Houston

pp. 2279

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On the Performance of the HONG Network for Pattern Classification (Abstract)

Ajantha S. Atukorale, University of Queensland

Tom Downs, University of Queensland

P.N. Suganthan, Nanyang Technological University

pp. 2285

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Incorporating a priori Knowledge into Initialized Weights for Neural Classifier (Abstract)

Zhe Chen, Ocean University of Qingdao

Tian-Jin Feng, Ocean University of Qingdao

Zweitze Houkes, Twente University

pp. 2291

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Combining Neural Networks, Fuzzy Sets, and Evidence Theory Based Approaches for Analyzing Color Images (Abstract)

Antanas Verikas, Halmstad University and Kaunas University of Technology

Kerstin Malmqvist, Halmstad University

Marija Bacauskiene, Kaunas University of Technology

pp. 2297

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