Algorithmic Learning Theory

21st International Conference, ALT 2010, Canberra, Australia, October 6-8, 2010. Proceedings

  • Marcus Hutter
  • Frank Stephan
  • Vladimir Vovk
  • Thomas Zeugmann
Conference proceedings ALT 2010
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6331)

Table of contents

  1. Front Matter
  2. Editors’ Introduction

    1. Marcus Hutter, Frank Stephan, Vladimir Vovk, Thomas Zeugmann
      Pages 1-10
  3. Invited Papers

  4. Regular Contributions

    1. Statistical Learning

      1. Liu Yang, Steve Hanneke, Jaime Carbonell
        Pages 50-58
      2. Wei Gao, Zhi-Hua Zhou
        Pages 59-73
    2. Grammatical Inference and Graph Learning

      1. Raphaël Bailly, Amaury Habrard, François Denis
        Pages 74-88
      2. Balázs Csanád Csáji, Raphaël M. Jungers, Vincent D. Blondel
        Pages 89-103
      3. Dana Angluin, James Aspnes, Lev Reyzin
        Pages 104-118
    3. Probably Approximately Correct Learning

      1. Guy Lever, François Laviolette, John Shawe-Taylor
        Pages 119-133
      2. Matthew Higgs, John Shawe-Taylor
        Pages 148-162
      3. Jiawei Lv, Jianwen Zhang, Fei Wang, Zheng Wang, Changshui Zhang
        Pages 163-178
    4. Query Learning and Algorithmic Teaching

      1. Borja Balle, Jorge Castro, Ricard Gavaldà
        Pages 179-193
      2. Dana Angluin, David Eisenstat, Leonid (Aryeh) Kontorovich, Lev Reyzin
        Pages 194-208
      3. Thorsten Doliwa, Hans Ulrich Simon, Sandra Zilles
        Pages 209-223

About these proceedings

Introduction

This volume contains the papers presented at the 21st International Conf- ence on Algorithmic Learning Theory (ALT 2010), which was held in Canberra, Australia, October 6–8, 2010. The conference was co-located with the 13th - ternational Conference on Discovery Science (DS 2010) and with the Machine Learning Summer School, which was held just before ALT 2010. The tech- cal program of ALT 2010, contained 26 papers selected from 44 submissions and ?ve invited talks. The invited talks were presented in joint sessions of both conferences. ALT 2010 was dedicated to the theoretical foundations of machine learning and took place on the campus of the Australian National University, Canberra, Australia. ALT provides a forum for high-quality talks with a strong theore- cal background and scienti?c interchange in areas such as inductive inference, universal prediction, teaching models, grammatical inference, formal languages, inductive logic programming, query learning, complexity of learning, on-line learning and relative loss bounds, semi-supervised and unsupervised learning, clustering,activelearning,statisticallearning,supportvectormachines,Vapnik- Chervonenkisdimension,probablyapproximatelycorrectlearning,Bayesianand causal networks, boosting and bagging, information-based methods, minimum descriptionlength,Kolmogorovcomplexity,kernels,graphlearning,decisiontree methods, Markov decision processes, reinforcement learning, and real-world - plications of algorithmic learning theory. DS 2010 was the 13th International Conference on Discovery Science and focused on the development and analysis of methods for intelligent data an- ysis, knowledge discovery and machine learning, as well as their application to scienti?c knowledge discovery. As is the tradition, it was co-located and held in parallel with Algorithmic Learning Theory.

Keywords

algorithmic learning theory algorithms classification complexity complexity theory decision trees grammtical inference inductive inference kolmogorov complexity logic programming query learning statistical learn support vector machines teaching models unsupervised learning

Editors and affiliations

  • Marcus Hutter
    • 1
  • Frank Stephan
    • 2
  • Vladimir Vovk
    • 3
  • Thomas Zeugmann
    • 4
  1. 1.Research School of Information Sciences and EngineeringAustralian National University and NICTACanberraAustralia
  2. 2.Department of MathematicsNational University of SingaporeSingaporeRepublic of Singapore
  3. 3.Department of Computer ScienceUniversity of London, Royal HollowayEgham, SurreyUK
  4. 4.Division of Computer ScienceHokkaido University, , ,Japan

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-642-16108-7
  • Copyright Information Springer-Verlag Berlin Heidelberg 2010
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Computer Science
  • Print ISBN 978-3-642-16107-0
  • Online ISBN 978-3-642-16108-7
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • About this book