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Table of contents

  1. Front Matter
  2. Filippo Neri, Lorenza Saitta
    Pages 20-27
  3. David W. Aha, Stephane Lapointe, Charles X. Ling, Stan Matwin
    Pages 29-48
  4. Yoram Biberman
    Pages 49-63
  5. Johannes Fürnkranz
    Pages 122-137
  6. Jürgen Herrmann, Reiner Ackermann, Jörg Peters, Detlef Reipa
    Pages 138-153
  7. Donate Malerba, Giovanni Semeraro, Floriana Esposito
    Pages 198-216
  8. S. H. Nienhuys-Cheng, M. Polman
    Pages 217-230
  9. Jonathan J. Oliver, David Hand
    Pages 231-241
  10. Michèle Sebag
    Pages 257-271
  11. Eleni Stroulia, Ashok K. Goel
    Pages 287-306
  12. Patrick R. J. van der Laag, Shan-Hwei Nienhuys-Cheng
    Pages 307-322
  13. Sašo Džeroski, Igor Petrovski
    Pages 347-350
  14. Tapio Elomaa, Esko Ukkonen
    Pages 351-354
  15. Claudio Ferretti, Giancarlo Mauri
    Pages 355-358
  16. D. Gunetti, U. Trinchero
    Pages 359-362
  17. Eizyu Hirowatari, Setsuo Arikawa
    Pages 363-366
  18. P. Jappy, M. C. Daniel-Vatonne, O. Gascuel, C. de la Higuera
    Pages 367-370
  19. A. Ketterlin, J. J. Korczak
    Pages 371-374
  20. Jyrki Kivinen, Heikki Mannila, Esko Ukkonen, Jaak Vilo
    Pages 375-378
  21. Ulrich Knoll, Gholamreza Nakhaeizadeh, Birgit Tausend
    Pages 383-386
  22. W. Z. Liu, A. P. White, M. T. Hallissey
    Pages 391-394
  23. Joel D. Martin
    Pages 395-398
  24. Dunja Mladenić, Ivan Bratko, Ray J. Paul, Marko Grobelnik
    Pages 399-402
  25. Janos Sarbo, József Farkas
    Pages 407-410
  26. Barbara Schulmeister, Fritz Wysotzki
    Pages 411-414
  27. Christel Vrain, Lionel Martin
    Pages 435-438
  28. Back Matter

About these proceedings

Introduction

This volume contains the proceedings of the European Conference on Machine Learning 1994, which continues the tradition of earlier meetings and which is a major forum for the presentation of the latest and most significant results in machine learning.
Machine learning is one of the most important subfields of artificial intelligence and computer science, as it is concerned with the automation of learning processes.
This volume contains two invited papers, 19 regular papers, and 25 short papers carefully reviewed and selected from in total 88 submissions.
The papers describe techniques, algorithms, implementations, and experiments in the area of machine learning.

Keywords

Algorithmic Learning Algorithmisches Lernen Inductive Learning Inductive Logic Programming Induktives Lernen Induktives logisches Programmieren Multi-strategy Learning artificial intelligence automation classification complexity genetic programming knowledge representation learning machine learning

Bibliographic information

  • DOI https://doi.org/10.1007/3-540-57868-4
  • Copyright Information Springer-Verlag Berlin Heidelberg 1994
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-540-57868-0
  • Online ISBN 978-3-540-48365-6
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • Buy this book on publisher's site