© 2006

Learning Theory

19th Annual Conference on Learning Theory, COLT 2006, Pittsburgh, PA, USA, June 22-25, 2006. Proceedings

  • Gábor Lugosi
  • Hans Ulrich Simon
Conference proceedings COLT 2006

Part of the Lecture Notes in Computer Science book series (LNCS, volume 4005)

Also part of the Lecture Notes in Artificial Intelligence book sub series (LNAI, volume 4005)

Table of contents

  1. Front Matter
  2. Invited Presentations

    1. Luc Devroye
      Pages 1-1
    2. György Turán
      Pages 2-3
    3. Vladimir Vovk
      Pages 4-4
  3. Clustering, Un-, and Semisupervised Learning

    1. Shai Ben-David, Ulrike von Luxburg, Dávid Pál
      Pages 5-19
    2. Jon Feldman, Rocco A. Servedio, Ryan O’Donnell
      Pages 20-34
    3. Ran El-Yaniv, Dmitry Pechyony
      Pages 35-49
  4. Statistical Learning Theory

    1. Ingo Steinwart, Don Hush, Clint Scovel
      Pages 79-93
    2. Magalie Fromont, Christine Tuleau
      Pages 94-108
  5. Regularized Learning and Kernel Methods

    1. Miroslav Dudík, Robert E. Schapire
      Pages 123-138
    2. Ha Quang Minh, Partha Niyogi, Yuan Yao
      Pages 154-168
    3. Nathan Srebro, Shai Ben-David
      Pages 169-183
  6. Query Learning and Teaching

    1. Laurence Bisht, Nader H. Bshouty, Hanna Mazzawi
      Pages 184-198
    2. Nader H. Bshouty, Hanna Mazzawi
      Pages 199-213
    3. Homin K. Lee, Rocco A. Servedio, Andrew Wan
      Pages 214-228
    4. Frank J. Balbach, Thomas Zeugmann
      Pages 229-243

About these proceedings


Clustering stability Support Vector Machine algorithmic learning classification computational learning decision theory game theory inductive inference kernel method kernel methods learning methods machine learning reinforcement learning stability supervised learning

Editors and affiliations

  • Gábor Lugosi
    • 1
  • Hans Ulrich Simon
    • 2
  1. 1.ICREA and Department of EconomicsUniversitat Pompeu FabraBarcelonaSpain
  2. 2.Ruhr-Universität BochumGermany

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