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Discovery Science

5th International Conference, DS 2002, Lubeck, Germany, November 24-26, 2002, Proceedings

  • Conference proceedings
  • © 2002

Overview

Editors:
  1. Steffen Lange

    1. Deutsches Forschungszentrum für Künstliche Intelligenz, Saarbrücken, Germany

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  2. Ken Satoh

    1. National Institute of Informatics, Tokyo, Japan

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    You can also search for this editor in PubMed   Google Scholar

  3. Carl H. Smith

    1. Department of Computer Science, University of Maryland, Maryland, USA

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 2534)

Included in the following conference series:

Conference proceedings info: DS 2002.

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Table of contents (49 papers)

  1. Front Matter

    Pages I-XIII
    Download chapter PDF

  2. Invited Talks

    1. Mathematics Based on Learning

      • Susumu Hayashi
      Pages 1-1

    2. Data Mining with Graphical Models

      • Rudolf Kruse, Christian Borgelt
      Pages 2-11

    3. On the Eigenspectrum of the Gram Matrix and Its Relationship to the Operator Eigenspectrum

      • John Shawe-Taylor, Chris Williams, Nello Cristianini, Jaz Kandola
      Pages 12-12

    4. In Search of the Horowitz Factor: Interim Report on a Musical Discovery Project

      • Gerhard Widmer
      Pages 13-32

    5. Learning Structure from Sequences, with Applications in a Digital Library

      • Ian H. Witten
      Pages 33-33

  3. Regular Papers

    1. Application of Discovery to Natural Science

      1. Discovering Frequent Structured Patterns from String Databases: An Application to Biological Sequences
        • Luigi Palopoli, Giorgio Terracina
        Pages 34-46
      2. Discovery in Hydrating Plaster Using Machine Learning Methods
        • Judith E. Devaney, John G. Hagedorn
        Pages 47-58
      3. Revising Qualitative Models of Gene Regulation
        • Kazumi Saito, Stephen Bay, Pat Langley
        Pages 59-70

    2. Knowledge Discovery from Unstructured and Semi-structured Data

      1. SEuS: Structure Extraction Using Summaries
        • Shayan Ghazizadeh, Sudarshan S. Chawathe
        Pages 71-85
      2. Discovering Best Variable-Length-Don’t-Care Patterns
        • Shunsuke Inenaga, Hideo Bannai, Ayumi Shinohara, Masayuki Takeda, Setsuo Arikawa
        Pages 86-97

    3. Meta-learning and Analysis of Machine Learning Algorithms

      1. A Study on the Effiect of Class Distribution Using Cost-Sensitive Learning
        • Kai Ming Ting
        Pages 98-112
      2. Model Complexity and Algorithm Selection in Classification
        • Melanie Hilario
        Pages 113-126
      3. Experiments with Projection Learning
        • Tapio Elomaa, J.T. Lindgren
        Pages 127-140
      4. Improved Dataset Characterisation for Meta-learning
        • Yonghong Peng, Peter A. Flach, Carlos Soares, Pavel Brazdil
        Pages 141-152

    4. Combining Machine Learning Algorithms

      1. Racing Committees for Large Datasets
        • Eibe Frank, Geoffrey Holmes, Richard Kirkby, Mark Hall
        Pages 153-164
      2. From Ensemble Methods to Comprehensible Models
        • C. Ferri, J. Hernández-Orallo, M. J. Ramírez-Quintana
        Pages 165-177

    5. Neural Networks and Statistical Methods

      1. Learning the Causal Structure of Overlapping Variable Sets
        • David Danks
        Pages 178-191
      2. Extraction of Logical Rules from Data by Means of Piecewise-Linear Neural Networks
        • Martin Holeňa
        Pages 192-205
      3. Structuring Neural Networks through Bidirectional Clustering of Weights
        • Kazumi Saito, Ryohei Nakano
        Pages 206-219
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  1. Discovery Science

Keywords

Editors and Affiliations

  • Deutsches Forschungszentrum für Künstliche Intelligenz, Saarbrücken, Germany

    Steffen Lange

  • National Institute of Informatics, Tokyo, Japan

    Ken Satoh

  • Department of Computer Science, University of Maryland, Maryland, USA

    Carl H. Smith

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