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

About these proceedings


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.


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
  • 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
  • About this book