© 2002

Machine Learning: ECML 2002

13th European Conference on Machine Learning Helsinki, Finland, August 19–23, 2002 Proceedings

  • Tapio Elomaa
  • Heikki Mannila
  • Hannu Toivonen
Conference proceedings ECML 2002

Part of the Lecture Notes in Computer Science book series (LNCS, volume 2430)

Also part of the Lecture Notes in Artificial Intelligence book sub series (LNAI, volume 2430)

Table of contents

  1. Front Matter
    Pages I-XIII
  2. Contributed Papers

    1. Bikramjit Banerjee, Jing Peng
      Pages 1-9
    2. Stephen D. Bay, Daniel G. Shapiro, Pat Langley
      Pages 10-22
    3. Xavier Carreras, Lluís Màrquez, Vasin Punyakanok, Dan Roth
      Pages 35-47
    4. Philip Derbeko, Ran El-Yaniv, Ron Meir
      Pages 60-72
    5. Yaakov Engel, Shie Mannor, Ron Meir
      Pages 84-96
    6. Johannes Fürnkranz
      Pages 97-110
    7. Geoffrey Holmes, Bernhard Pfahringer, Richard Kirkby, Eibe Frank, Mark Hall
      Pages 161-172
    8. Eyke Hüllermeier
      Pages 173-184
    9. Stefan Klink, Armin Hust, Markus Junker, Andreas Dengel
      Pages 195-207
    10. Tony Kr°akenes, Ole Martin Halck
      Pages 207-218
    11. Matjaž Kukar, Igor Kononenko
      Pages 219-231

Other volumes

  1. Machine Learning: ECML 2002
    13th European Conference on Machine Learning Helsinki, Finland, August 19–23, 2002 Proceedings
  2. 6th European Conference, PKDD 2002 Helsinki, Finland, August 19–23, 2002 Proceedings

About these proceedings


This book constitutes the refereed preceedings of the 13th European Conference on Machine Learning, ECML 2002, held in Helsinki, Finland in August 2002.
The 41 revised full papers presented together with 4 invited contributions were carefully reviewed and selected from numerous submissions. Among the topics covered are computational discovery, search strategies, Classification, support vector machines, kernel methods, rule induction, linear learning, decision tree learning, boosting, collaborative learning, statistical learning, clustering, instance-based learning, reinforcement learning, multiagent learning, multirelational learning, Markov decision processes, active learning, etc.


Boosting Markov decision process Support Vector Machine classification kernel method learning machine learning reinforcement learning

Editors and affiliations

  • Tapio Elomaa
    • 1
  • Heikki Mannila
    • 1
  • Hannu Toivonen
    • 1
  1. 1.Department of Computer ScienceUniversity of HelsinkiHelsinkiFinland

Bibliographic information

Industry Sectors
Chemical Manufacturing
IT & Software
Consumer Packaged Goods
Materials & Steel
Finance, Business & Banking
Energy, Utilities & Environment
Oil, Gas & Geosciences