Algorithmic Learning Theory: 17th International Conference, ALT 2006, Barcelona, Spain, October 7-10, 2006, Proceedings | SpringerLink
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Algorithmic Learning Theory

17th International Conference, ALT 2006, Barcelona, Spain, October 7-10, 2006, Proceedings

  • Conference proceedings
  • © 2006

Overview

Editors:
  1. José L. Balcázar

    1. Departament de Llenguatges i Sistemes Informàtics Laboratori d’Algorísmica Relacional, Complexitat i Aprenentatge, Universitat Politècnica de Catalunya, Barcelona,  

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  2. Philip M. Long

    1. Google, Mountain View, USA

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    You can also search for this editor in PubMed   Google Scholar

  3. Frank Stephan

    1. Department of Computer Science and Department of Mathematics, National University of Singapore, Singapore, Republic of Singapore

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    You can also search for this editor in PubMed   Google Scholar

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 4264)

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

Included in the following conference series:

Conference proceedings info: ALT 2006.

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Keywords

Table of contents (30 papers)

  1. Front Matter

    Download chapter PDF

  2. Editors’ Introduction

    1. Editors’ Introduction

      • Jose L. Balcázar, Philip M. Long, Frank Stephan
      Pages 1-9

  4. Regular Contributions

    1. Learning Unions of ω(1)-Dimensional Rectangles

      • Alp Atıcı, Rocco A. Servedio
      Pages 32-47

    2. On Exact Learning Halfspaces with Random Consistent Hypothesis Oracle

      • Nader H. Bshouty, Ehab Wattad
      Pages 48-62

    3. Active Learning in the Non-realizable Case

      • Matti Kääriäinen
      Pages 63-77

    4. How Many Query Superpositions Are Needed to Learn?

      • Jorge Castro
      Pages 78-92

    5. Teaching Memoryless Randomized Learners Without Feedback

      • Frank J. Balbach, Thomas Zeugmann
      Pages 93-108

    6. The Complexity of Learning SUBSEQ (A)

      • Stephen Fenner, William Gasarch
      Pages 109-123

    7. Mind Change Complexity of Inferring Unbounded Unions of Pattern Languages from Positive Data

      • Matthew de Brecht, Akihiro Yamamoto
      Pages 124-138

    8. Learning and Extending Sublanguages

      • Sanjay Jain, Efim Kinber
      Pages 139-153

    9. Iterative Learning from Positive Data and Negative Counterexamples

      • Sanjay Jain, Efim Kinber
      Pages 154-168

    10. Towards a Better Understanding of Incremental Learning

      • Sanjay Jain, Steffen Lange, Sandra Zilles
      Pages 169-183

    11. On Exact Learning from Random Walk

      • Nader H. Bshouty, Iddo Bentov
      Pages 184-198

    12. Risk-Sensitive Online Learning

      • Eyal Even-Dar, Michael Kearns, Jennifer Wortman
      Pages 199-213

    13. Leading Strategies in Competitive On-Line Prediction

      • Vladimir Vovk
      Pages 214-228
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Other volumes

  1. Algorithmic Learning Theory

Editors and Affiliations

  • Departament de Llenguatges i Sistemes Informàtics Laboratori d’Algorísmica Relacional, Complexitat i Aprenentatge, Universitat Politècnica de Catalunya, Barcelona,  

    José L. Balcázar

  • Google, Mountain View, USA

    Philip M. Long

  • Department of Computer Science and Department of Mathematics, National University of Singapore, Singapore, Republic of Singapore

    Frank Stephan

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