Advertisement

Table of contents

  1. Front Matter
  2. Stuart Russell
    Pages 1-3
  3. Paul Vitányi, Ming Li
    Pages 14-30
  4. Eva Armengol, Enric Plaza
    Pages 31-48
  5. Luc De Raedt, Peter Idestam-Almquist, Gunther Sablon
    Pages 73-84
  6. Gülşen Demiröz, H. Altay Güvenir
    Pages 85-92
  7. Janez Demšar, Blaž Zupan, Marko Bohanec, Ivan Bratko
    Pages 93-107
  8. Dragan Gamberger, Nada Lavrač
    Pages 108-123
  9. Alan Hutchinson
    Pages 138-145
  10. Miroslav Kubat, Robert Holte, Stan Matwin
    Pages 146-153
  11. Nicolas Lachiche, Pierre Marquis
    Pages 154-161
  12. Lionel Martin, Christel Vrain
    Pages 162-169
  13. Nikolay I. Nikolaev, Vanio Slavov
    Pages 183-190
  14. Tim Oates, Matthew D. Schmill, Paul R. Cohen
    Pages 191-198
  15. Bernhard Pfahringer
    Pages 199-212
  16. Rafał Sałustowicz, Jürgen Schmidhuber
    Pages 213-220
  17. Ning Shan, Howard J. Hamilton, Nick Cercone
    Pages 234-241
  18. Kai Ming Ting, Boon Toh Low
    Pages 250-265
  19. Luís Torgo, João Gama
    Pages 266-273
  20. Fabien Torre, Céline Rouveirol
    Pages 274-289
  21. K. Vanhoof, Josee Bloemer, K. Pauwels
    Pages 290-297
  22. Cristina Versino, Luca Maria Gambardella
    Pages 298-311
  23. Ricardo Vilalta, Gunnar Blix, Larry Rendell
    Pages 312-326
  24. David W. Aha, Dietrich Wettschereck
    Pages 327-336
  25. Walter Daelemans, Antal van den Bosch, Ton Weijters
    Pages 337-344
  26. Michael Kaiser, Volker Klingspor, Holger Friedrich
    Pages 345-352
  27. Back Matter

Other volumes

  1. Machine Learning: ECML-97
    9th European Conference on Machine Learning Prague, Czech Republic, April 23–25, 1997 Proceedings
  2. First European Symposium, PKDD '97 Trondheim, Norway, June 24–27, 1997 Proceedings

About these proceedings

Introduction

This book constitutes the refereed proceedings of the Ninth European Conference on Machine Learning, ECML-97, held in Prague, Czech Republic, in April 1997.
This volume presents 26 revised full papers selected from a total of 73 submissions. Also included are an abstract and two papers corresponding to the invited talks as well as descriptions from four satellite workshops. The volume covers the whole spectrum of current machine learning issues.

Keywords

Algorithmisches lernen Entscheidungstheorie Induktives Logisches Programmieren Lernende Agenten Maschinelles Lernen algorithmic learning classification decision making genetic programming inductive logic programming learning logic machine learning programming reinforcement learning

Bibliographic information

  • DOI https://doi.org/10.1007/3-540-62858-4
  • Copyright Information Springer-Verlag Berlin Heidelberg 1997
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-540-62858-3
  • Online ISBN 978-3-540-68708-5
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • Buy this book on publisher's site