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Learning Theory

20th Annual Conference on Learning Theory, COLT 2007, San Diego, CA, USA; June 13-15, 2007. Proceedings

  • Editors
  • Nader H. Bshouty
  • Claudio Gentile

Part of the Lecture Notes in Computer Science book series (LNCS, volume 4539)

Also part of the Lecture Notes in Artificial Intelligence book sub series (LNAI, volume 4539)

Table of contents

  1. Front Matter
  2. Invited Presentations

  3. Unsupervised, Semisupervised and Active Learning I

    1. Rui M. Castro, Robert D. Nowak
      Pages 5-19
    2. Shai Ben-David, Dávid Pál, Hans Ulrich Simon
      Pages 20-34
    3. Maria-Florina Balcan, Andrei Broder, Tong Zhang
      Pages 35-50
  4. Unsupervised, Semisupervised and Active Learning II

    1. Dana Angluin, James Aspnes, Jiang Chen, Lev Reyzin
      Pages 51-65
    2. Sham M. Kakade, Dean P. Foster
      Pages 82-96
  5. Statistical Learning Theory

    1. Arnak S. Dalalyan, Alexandre B. Tsybakov
      Pages 97-111
    2. Gilles Blanchard, François Fleuret
      Pages 112-126
    3. Sylvain Arlot, Gilles Blanchard, Étienne Roquain
      Pages 127-141
    4. Ran El-Yaniv, Dmitry Pechyony
      Pages 157-171
  6. Inductive Inference

    1. John Case, Samuel E. Moelius III
      Pages 172-186
    2. Oliver Schulte, Wei Luo, Russell Greiner
      Pages 187-202
    3. Lorenzo Carlucci, John Case, Sanjay Jain
      Pages 203-217
    4. Sanjay Jain, Frank Stephan
      Pages 218-232
  7. Online and Reinforcement Learning I

    1. Eyal Even-Dar, Michael Kearns, Yishay Mansour, Jennifer Wortman
      Pages 233-247
    2. Gábor Lugosi, Shie Mannor, Gilles Stoltz
      Pages 248-262
  8. Online and Reinforcement Learning II

    1. Sanjoy Dasgupta, Daniel Hsu
      Pages 278-292
    2. Yuri Kalnishkan, Vladimir Vovk, Michael V. Vyugin
      Pages 293-307
    3. Francisco S. Melo, M. Isabel Ribeiro
      Pages 308-322
  9. Regularized Learning, Kernel Methods, SVM

    1. Nikolas List, Don Hush, Clint Scovel, Ingo Steinwart
      Pages 336-348
    2. Corinna Cortes, Leonid Kontorovich, Mehryar Mohri
      Pages 349-364
  10. Learning Algorithms and Limitations on Learning

    1. Alexandre Belloni, Robert M. Freund, Santosh S. Vempala
      Pages 393-408
    2. Adam R. Klivans, Alexander A. Sherstov
      Pages 409-423
    3. Sudipto Guha, Piotr Indyk, Andrew McGregor
      Pages 424-438
  11. Online and Reinforcement Learning III

    1. Peter Auer, Ronald Ortner, Csaba Szepesvári
      Pages 454-468
    2. David P. Helmbold, Manfred K. Warmuth
      Pages 469-483
  12. Online and Reinforcement Learning IV

    1. Jacob Abernethy, Peter Bartlett, Alexander Rakhlin
      Pages 484-498
    2. Elad Hazan, Nimrod Megiddo
      Pages 499-513
  13. Dimensionality Reduction

    1. Florentina Bunea, Alexandre B. Tsybakov, Marten H. Wegkamp
      Pages 530-543
    2. Saharon Rosset, Grzegorz Swirszcz, Nathan Srebro, Ji Zhu
      Pages 544-558
  14. Other Approaches

    1. Julian Lorenz, Martin Marciniszyn, Angelika Steger
      Pages 574-588
    2. Marcus Hutter
      Pages 589-603
    3. Maria-Florina Balcan, Nikhil Bansal, Alina Beygelzimer, Don Coppersmith, John Langford, Gregory B. Sorkin
      Pages 604-619
  15. Open Problems

    1. Liwei Wang, Jufu Feng
      Pages 620-621
    2. Avrim Blum, Maria-Florina Balcan
      Pages 622-624
    3. Pallika Kanani, Andrew McCallum
      Pages 625-627
    4. Manfred K. Warmuth
      Pages 630-632
  16. Back Matter

About these proceedings

Keywords

Alphabet active learning algorithm algorithmic learning algorithms classification complexity computational learning decision theory game theory inductive inference kernel method machine learning optimization stability

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-540-72927-3
  • Copyright Information Springer-Verlag Berlin Heidelberg 2007
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Computer Science
  • Print ISBN 978-3-540-72925-9
  • Online ISBN 978-3-540-72927-3
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • Buy this book on publisher's site