Algorithmic Learning Theory

20th International Conference, ALT 2009, Porto, Portugal, October 3-5, 2009. Proceedings

  • Ricard Gavaldà
  • Gábor Lugosi
  • Thomas Zeugmann
  • Sandra Zilles
Conference proceedings ALT 2009

Part of the Lecture Notes in Computer Science book series (LNCS, volume 5809)

Also part of the Lecture Notes in Artificial Intelligence book sub series (LNAI, volume 5809)

Table of contents

  1. Front Matter
  2. Invited Papers

  3. Regular Contributions

    1. Online Learning

      1. Alexey Chernov, Vladimir Vovk
        Pages 8-22
      2. Sébastien Bubeck, Rémi Munos, Gilles Stoltz
        Pages 23-37
      3. László Györfi, Péter Kevei
        Pages 83-96
    2. Learning Graphs

      1. Nader H. Bshouty, Hanna Mazzawi
        Pages 97-109
      2. Nicolò Cesa-Bianchi, Claudio Gentile, Fabio Vitale
        Pages 110-125
      3. Tatsuya Akutsu, Takeyuki Tamura, Katsuhisa Horimoto
        Pages 126-140
    3. Active Learning and Query Learning

      1. Andrew Guillory, Jeff Bilmes
        Pages 141-155
      2. Marta Arias, José L. Balcázar
        Pages 156-170
      3. Dana Angluin, Leonor Becerra-Bonache, Adrian Horia Dediu, Lev Reyzin
        Pages 171-185
      4. Ricard Gavaldà, Denis Thérien
        Pages 201-215

About these proceedings


This book constitutes the refereed proceedings of the 20th International Conference on Algorithmic Learning Theory, ALT 2009, held in Porto, Portugal, in October 2009, co-located with the 12th International Conference on Discovery Science, DS 2009.

The 26 revised full papers presented together with the abstracts of 5 invited talks were carefully reviewed and selected from 60 submissions. The papers are divided into topical sections of papers on online learning, learning graphs, active learning and query learning, statistical learning, inductive inference, and semisupervised and unsupervised learning. The volume also contains abstracts of the

invited talks: Sanjoy Dasgupta, The Two Faces of Active Learning; Hector Geffner, Inference and

Learning in Planning; Jiawei Han, Mining Heterogeneous; Information Networks By Exploring the Power of Links, Yishay Mansour, Learning and Domain Adaptation; Fernando C.N. Pereira, Learning on the Web.


active learning algorithms boolean function learning complexity data mining half-space learning iterative learning language learning learning machine learning query learning tensor clustering visualization

Editors and affiliations

  • Ricard Gavaldà
    • 1
  • Gábor Lugosi
    • 2
  • Thomas Zeugmann
    • 3
  • Sandra Zilles
    • 4
  1. 1.Research Group, Departament de Llenguatges i Sistemes InformàticsUniversitat Politècnica de Catalunya,BarcelonaSpain
  2. 2.ICREA and Department of EconomicsPompeu Fabra UniversitatBarcelonaSpain
  3. 3.Division of Computer ScienceHokkaido UniversitySapporoJapan
  4. 4.Department of Computer ScienceUniversity of ReginaReginaCanada

Bibliographic information

  • DOI
  • Copyright Information Springer-Verlag Berlin Heidelberg 2009
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Computer Science
  • Print ISBN 978-3-642-04413-7
  • Online ISBN 978-3-642-04414-4
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • About this book