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© 1999

Algorithmic Learning Theory

10th International Conference, ALT’99 Tokyo, Japan, December 6–8, 1999 Proceedings

  • Osamu Watanabe
  • Takashi Yokomori
Conference proceedings ALT 1999

Part of the Lecture Notes in Computer Science book series (LNCS, volume 1720)

Also part of the Lecture Notes in Artificial Intelligence book sub series (LNAI, volume 1720)

Table of contents

  1. Front Matter
    Pages I-XI
  2. Invited Lectures

  3. Regular Contributions

    1. Neural Networks

    2. Learning Dimension

      1. José L. Balcázar, Jorge Castro, David Guijarro, Hans-Ulrich Simon
        Pages 77-92
      2. Andrew Mitchell, Tobias Scheffer, Arun Sharma, Frank Stephan
        Pages 93-105
      3. Theodoros Evgeniou, Massimiliano Pontil
        Pages 106-117
    3. Inductive Inference

      1. Steffen Lange, Gunter Grieser
        Pages 118-131
      2. Peter Rossmanith
        Pages 132-144
      3. Phil Watson
        Pages 145-156
    4. Inductive Logic Programming

    5. PAC Learning

      1. Nader H. Bshouty, Nadav Eiron, Eyal Kushilevitz
        Pages 206-218
      2. Francesco De Comité, François Denis, Rémi Gilleron, Fabien Letouzey
        Pages 219-230

About these proceedings

Keywords

Algorithmic Learning Boosting Data Mining Formal Languages Inductive Inference Inductive Logic Programming Support Vector Machine Variable algorithmic learning theory algorithms complexity learning learning theory logic reinforcement learning

Editors and affiliations

  • Osamu Watanabe
    • 1
  • Takashi Yokomori
    • 2
  1. 1.Department of Mathematical and Computing SciencesTokyo Institute of TechnologyTokyoJapan
  2. 2.Waseda UniversityTokyoJapan

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