Algorithmic Learning Theory

14th International Conference, ALT 2003, Sapporo, Japan, October 17-19, 2003. Proceedings

  • Ricard Gavaldá
  • Klaus P. Jantke
  • Eiji Takimoto

Part of the Lecture Notes in Computer Science book series (LNCS, volume 2842)

Also part of the Lecture Notes in Artificial Intelligence book sub series (LNAI, volume 2842)

Table of contents

  1. Front Matter
  2. Invited Papers

  3. Inductive Inference

  4. Learning and Information Extraction

    1. Jan Arpe, Rüdiger Reischuk
      Pages 99-113
    2. Yusuke Suzuki, Takayoshi Shoudai, Satoshi Matsumoto, Tomoyuki Uchida, Tetsuhiro Miyahara
      Pages 114-128
  5. Learning with Queries

    1. Steffen Lange, Sandra Zilles
      Pages 129-143
    2. Satoshi Matsumoto, Yusuke Suzuki, Takayoshi Shoudai, Tetsuhiro Miyahara, Tomoyuki Uchida
      Pages 144-158
  6. Learning with Non-linear Optimization

    1. Jingdong Wang, Jianguo Lee, Changshui Zhang
      Pages 159-174
    2. Tijl De Bie, Michinari Momma, Nello Cristianini
      Pages 175-189
    3. Shaojun Wang, Dale Schuurmans
      Pages 190-204
  7. Learning from Random Examples

    1. John Case, Sanjay Jain, Rüdiger Reischuk, Frank Stephan, Thomas Zeugmann
      Pages 234-246

About these proceedings

Keywords

Variable algorithm algorithmic learning algorithmic learning theory algorithms complexity computational learning concept learning inductive inference knowledge discovery machine learning modeling neural network learning optimization support vector machines

Editors and affiliations

  • Ricard Gavaldá
    • 1
  • Klaus P. Jantke
    • 2
  • Eiji Takimoto
    • 3
  1. 1.Universitat Politècnica de CatalunyaBarcelonaSpain
  2. 2.Meme Media LaboratoryHokkaido University SapporoSapporoJapan
  3. 3.  

Bibliographic information

  • DOI https://doi.org/10.1007/b14273
  • Copyright Information Springer-Verlag Berlin Heidelberg 2003
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-540-20291-2
  • Online ISBN 978-3-540-39624-6
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • About this book