Advertisement

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
  7. Inductive Inference

    1. Lorenzo Carlucci, John Case, Sanjay Jain, Frank Stephan
      Pages 244-258
    2. François Denis, Yann Esposito, Amaury Habrard
      Pages 274-288
  8. Learning Algorithms and Limitations on Learning

  9. Online Aggregation

    1. Florentina Bunea, Alexandre B. Tsybakov, Marten H. Wegkamp
      Pages 379-391
  10. Online Prediction and Reinforcement Learning I

    1. Shie Mannor, Nahum Shimkin
      Pages 408-422
    2. Shai Shalev-Shwartz, Yoram Singer
      Pages 423-437
    3. Koby Crammer
      Pages 438-452
    4. Ofer Dekel, Philip M. Long, Yoram Singer
      Pages 453-467
  11. Online Prediction and Reinforcement Learning II

    1. András György, Tamás Linder, György Ottucsák
      Pages 468-482
    2. Nicolò Cesa-Bianchi, Claudio Gentile
      Pages 483-498
    3. Elad Hazan, Adam Kalai, Satyen Kale, Amit Agarwal
      Pages 499-513
    4. Manfred K. Warmuth, Dima Kuzmin
      Pages 514-528
  12. Online Prediction and Reinforcement Learning III

    1. Shie Mannor, John N. Tsitsiklis
      Pages 529-543
    2. Jacob Abernethy, John Langford, Manfred K. Warmuth
      Pages 544-558
    3. Vladimir Vovk
      Pages 559-573
  13. Other Approaches

    1. Cynthia Rudin
      Pages 589-604
    2. David Cossock, Tong Zhang
      Pages 605-619
    3. Shai Fine, Yishay Mansour
      Pages 620-634
    4. Ping Li, Trevor J. Hastie, Kenneth W. Church
      Pages 635-649
  14. Open Problems

  15. Back Matter

About these proceedings

Keywords

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

Bibliographic information

  • DOI https://doi.org/10.1007/11776420
  • Copyright Information Springer-Verlag Berlin Heidelberg 2006
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Computer Science
  • Print ISBN 978-3-540-35294-5
  • Online ISBN 978-3-540-35296-9
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • Buy this book on publisher's site