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Artificial Neural Networks: Formal Models and Their Applications – ICANN 2005

15th International Conference, Warsaw, Poland, September 11-15, 2005, Proceedings, Part II

  • Conference proceedings
  • © 2005

Overview

Editors:
  1. Włodzisław Duch

    1. Department of Informatics, Nicolaus Copernicus University, Toruń, Poland

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  2. Janusz Kacprzyk

    1. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

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  3. Erkki Oja

    1. Adaptive Informatics Research Centre, Helsinki University of Technology, HUT, Finland

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  4. Sławomir Zadrożny

    1. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 3697)

Part of the book sub series: Theoretical Computer Science and General Issues (LNTCS)

Included in the following conference series:

Conference proceedings info: ICANN 2005.

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Table of contents (163 papers)

  1. Ensemble-Based Learning

    1. Combination Methods for Ensembles of RBFs

      • Carlos Hernández-Espinosa, Joaquín Torres-Sospedra, Mercedes Fernández-Redondo
      Pages 121-126

    2. Ensemble Techniques for Credibility Estimation of GAME Models

      • Pavel Kordík, Miroslav Šnorek
      Pages 127-132

    3. Combination Methods for Ensembles of MF

      • Joaquín Torres-Sospedra, Mercedes Fernández-Redondo, Carlos Hernández-Espinosa
      Pages 133-138

    4. New Results on Ensembles of Multilayer Feedforward

      • Joaquín Torres-Sospedra, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo
      Pages 139-144

  2. Unsupervised Learning

    1. On Variations of Power Iteration

      • Seungjin Choi
      Pages 145-150

    2. Linear Dimension Reduction Based on the Fourth-Order Cumulant Tensor

      • M. Kawanabe
      Pages 151-156

    3. On Spectral Basis Selection for Single Channel Polyphonic Music Separation

      • Minje Kim, Seungjin Choi
      Pages 157-162

    4. Independent Subspace Analysis Using k-Nearest Neighborhood Distances

      • Barnabás Póczos, András Lőrincz
      Pages 163-168

  3. Recurrent Neural Networks

    1. Study of the Behavior of a New Boosting Algorithm for Recurrent Neural Networks

      • Mohammad Assaad, Romuald Boné, Hubert Cardot
      Pages 169-174

    2. Time Delay Learning by Gradient Descent in Recurrent Neural Networks

      • Romuald Boné, Hubert Cardot
      Pages 175-180

    3. Representation and Identification Method of Finite State Automata by Recurrent High-Order Neural Networks

      • Yasuaki Kuroe
      Pages 181-189

    4. Global Stability Conditions of Locally Recurrent Neural Networks

      • Krzysztof Patan, Józef Korbicz, Przemysław Prętki
      Pages 191-196

  4. Reinforcement Learning

    1. An Agent-Based PLA for the Cascade Correlation Learning Architecture

      • Ireneusz Czarnowski, Piotr Jędrzejowicz
      Pages 197-202

    2. Dual Memory Model for Using Pre-existing Knowledge in Reinforcement Learning Tasks

      • Kary Främling
      Pages 203-208

    3. Stochastic Processes for Return Maximization in Reinforcement Learning

      • Kazunori Iwata, Hideaki Sakai, Kazushi Ikeda
      Pages 209-214

    4. Maximizing the Ratio of Information to Its Cost in Information Theoretic Competitive Learning

      • Ryotaro Kamimura, Sachiko Aida-Hyugaji
      Pages 215-222

    5. Completely Self-referential Optimal Reinforcement Learners

      • Jürgen Schmidhuber
      Pages 223-233

    6. Model Selection Under Covariate Shift

      • Masashi Sugiyama, Klaus-Robert Müller
      Pages 235-240

  5. Bayesian Approaches to Learning

    1. Smooth Performance Landscapes of the Variational Bayesian Approach

      • Zhuo Gao, K. Y. Michael Wong
      Pages 241-246

    2. Jacobi Alternative to Bayesian Evidence Maximization in Diffusion Filtering

      • Ramūnas Girdziušas, Jorma Laaksonen
      Pages 247-252
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Other volumes

  1. Artificial Neural Networks: Biological Inspirations – ICANN 2005

  2. Artificial Neural Networks: Formal Models and Their Applications – ICANN 2005

Keywords

About this book

This volume is the first part of the two-volume proceedings of the International C- ference on Artificial Neural Networks (ICANN 2005), held on September 11–15, 2005 in Warsaw, Poland, with several accompanying workshops held on September 15, 2005 at the Nicolaus Copernicus University, Toru , Poland. The ICANN conference is an annual meeting organized by the European Neural Network Society in cooperation with the International Neural Network Society, the Japanese Neural Network Society, and the IEEE Computational Intelligence Society. It is the premier European event covering all topics concerned with neural networks and related areas. The ICANN series of conferences was initiated in 1991 and soon became the major European gathering for experts in those fields. In 2005 the ICANN conference was organized by the Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland, and the Nicolaus Copernicus Univ- sity, Toru , Poland. From over 600 papers submitted to the regular sessions and some 10 special c- ference sessions, the International Program Committee selected – after a thorough peer-review process – about 270 papers for publication. The large number of papers accepted is certainly a proof of the vitality and attractiveness of the field of artificial neural networks, but it also shows a strong interest in the ICANN conferences.

Editors and Affiliations

  • Department of Informatics, Nicolaus Copernicus University, Toruń, Poland

    Włodzisław Duch

  • Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

    Janusz Kacprzyk, Sławomir Zadrożny

  • Adaptive Informatics Research Centre, Helsinki University of Technology, HUT, Finland

    Erkki Oja

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