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Algorithmic Learning Theory

7th International Workshop, ALT '96, Sydney, Australia, October 23 - 25, 1996. Proceedings

  • Conference proceedings
  • © 1996

Overview

Editors:
  1. Setsuo Arikawa
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  2. Arun K. Sharma
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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 1160)

Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)

Included in the following conference series:

Conference proceedings info: ALT 1996.

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Table of contents (28 papers)

  1. Front Matter

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  2. Managing complexity in neuroidal circuits

    • Leslie G. Valiant
    Pages 1-11

  3. Learnability of exclusive-or expansion based on monotone DNF formulas

    • Eiji Takimoto, Yoshifumi Sakai, Akira Maruoka
    Pages 12-25

  4. Improved bounds about on-line learning of smooth functions of a single variable

    • Philip M. Long
    Pages 26-36

  5. Query learning of bounded-width OBDDs

    • Atsuyoshi Nakamura
    Pages 37-50

  6. Learning a representation for optimizable formulas

    • Hans Kleine Büning, Theodor Lettmann
    Pages 51-58

  7. Limits of exact algorithms for inference of minimum size finite state machines

    • Arlindo L. Oliveira, Stephen Edwards
    Pages 59-66

  8. Genetic fitness optimization using rapidly mixing Markov chains

    • Paul Vitányi
    Pages 67-82

  9. The kindest cut: Minimum message length segmentation

    • Rohan A. Baxter, Jonathan J. Oliver
    Pages 83-90

  10. Reducing complexity of decision trees with two variable tests

    • Pearson R. A., Smith E. K. T.
    Pages 91-99

  11. The complexity of exactly learning algebraic concepts

    • V. Arvind, N. V. Vinodchandran
    Pages 100-112

  12. Efficient learning of real time two-counter automata

    • Amr F. Fahmy, Robert S. Roos
    Pages 113-126

  13. Cost-sensitive feature reduction applied to a hybrid genetic algorithm

    • Nada Lavrač, Dragan Gamberger, Peter Turney
    Pages 127-134

  14. Effects of Feature Selection with ‘Blurring’ on neurofuzzy systems

    • Selwyn Piramuthu
    Pages 135-142

  15. Boosting first-order learning

    • J. R. Quinlan
    Pages 143-155

  16. Incorporating hypothetical knowledge into the process of inductive synthesis

    • Jānis Bārzdiņš, Ugis Sarkans
    Pages 156-168

  17. Induction of Constraint Logic Programs

    • Lionel Martin, Christel Vrain
    Pages 169-176

  18. Constructive learning of translations based on dictionaries

    • Noriko Sugimoto, Kouichi Hirata, Hiroki Ishizaka
    Pages 177-184

  19. Inductive logic programming beyond logical implication

    • Jianguo Lu, Jun Arima
    Pages 185-198

  20. Noise elimination in inductive concept learning: A case study in medical diagnosis

    • Dragan Gamberger, Nada Lavrač, Sašo Džeroski
    Pages 199-212
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  1. Algorithmic Learning Theory

Keywords

About this book

This book constitutes the refereed proceedings of the 7th International Workshop on Algorithmic Learning Theory, ALT '96, held in Sydney, Australia, in October 1996.
The 16 revised full papers presented were selected from 41 submissions; also included are eight short papers as well as four full length invited contributions by Ross Quinlan, Takeshi Shinohara, Leslie Valiant, and Paul Vitanyi, and an introduction by the volume editors. The book covers all areas related to algorithmic learning theory, ranging from theoretical foundations of machine learning to applications in several areas.

Bibliographic Information

  • Book Title: Algorithmic Learning Theory

  • Book Subtitle: 7th International Workshop, ALT '96, Sydney, Australia, October 23 - 25, 1996. Proceedings

  • Editors: Setsuo Arikawa, Arun K. Sharma

  • Series Title: Lecture Notes in Computer Science

  • DOI: https://doi.org/10.1007/3-540-61863-5

  • Publisher: Springer Berlin, Heidelberg

  • eBook Packages: Springer Book Archive

  • Copyright Information: Springer-Verlag Berlin Heidelberg 1996

  • Softcover ISBN: 978-3-540-61863-8Published: 09 October 1996

  • eBook ISBN: 978-3-540-70719-6Published: 14 July 2005

  • Series ISSN: 0302-9743

  • Series E-ISSN: 1611-3349

  • Edition Number: 1

  • Number of Pages: XVII, 337

  • Topics: Artificial Intelligence, Mathematical Logic and Formal Languages

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