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Computational Learning Theory

4th European Conference, EuroCOLT’99 Nordkirchen, Germany, March 29–31, 1999 Proceedings

  • Paul Fischer
  • Hans Ulrich Simon
Conference proceedings EuroCOLT 1999

Part of the Lecture Notes in Computer Science book series (LNCS, volume 1572)

Also part of the Lecture Notes in Artificial Intelligence book sub series (LNAI, volume 1572)

Table of contents

  1. Front Matter
    Pages I-X
    PDF

  2. Invited Lectures

    1. Theoretical Views of Boosting
      Robert E. Schapire
      Pages 1-10
    2. Open Theoretical Questions in Reinforcement Learning
      Richard S. Sutton
      Pages 11-17

  3. Learning from Random Examples

    1. A Geometric Approach to Leveraging Weak Learners
      Nigel Duffy, David Helmbold
      Pages 18-33
    2. Query by Committee, Linear Separation and Random Walks
      Ran Bachrach, Shai Fine, Eli Shamir
      Pages 34-49
    3. Hardness Results for Neural Network Approximation Problems
      Peter Bartlett, Shai Ben-David
      Pages 50-62

  4. Learning from Queries and Counterexamples

    1. Learnability of Quantified Formulas
      Víctor Dalmau, Peter Jeavons
      Pages 63-78
    2. Learning Multiplicity Automata from Smallest Counterexamples
      Jüurgen Forster
      Pages 79-90
    3. Exact Learning when Irrelevant Variables Abound
      David Guijarro, Víctor Lavín, Vijay Raghavan
      Pages 91-100
    4. An Application of Codes to Attribute-Efficient Learning
      Thomas Hofmeister
      Pages 101-110
    5. Learning Range Restricted Horn Expressions
      Roni Khardon
      Pages 111-125

  5. Reinforcement Learning

    1. On the Asymptotic Behavior of a Constant Stepsize Temporal-Difference Learning Algorithm
      Vladislav Tadić
      Pages 126-137

  6. On-line Learning and Expert Advice

    1. Direct and Indirect Algorithms for On-line Learning of Disjunctions
      D. P. Helmbold, S. Panizza, M. K. Warmuth
      Pages 138-152
    2. Averaging Expert Predictions
      Jyrki Kivinen, Manfred K. Warmuth
      Pages 153-167

  7. Teaching and Learning

    1. On Teaching and Learning Intersection-Closed Concept Classes
      Christian Kuhlmann
      Pages 168-182

  8. Inductive Inference

    1. Avoiding Coding Tricks by Hyperrobust Learning
      Matthias Ott, Frank Stephan
      Pages 183-197
    2. Mind Change Complexity of Learning Logic Programs
      Sanjay Jain, Arun Sharma
      Pages 198-213

  9. Statistical Theory of Learning and Pattern Recognition

    1. Regularized Principal Manifolds
      Alex J. Smola, Robert C. Williamson, Sebastian Mika, Bernhard Schölkopf
      Pages 214-229
    2. Distribution-Dependent Vapnik-Chervonenkis Bounds
      Nicolas Vayatis, Robert Azencott
      Pages 230-240
    3. Lower Bounds on the Rate of Convergence of Nonparametric Pattern Recognition
      András Antos
      Pages 241-252
    4. On Error Estimation for the Partitioning Classification Rule
      Márta Horváth
      Pages 253-262
    5. Margin Distribution Bounds on Generalization
      John Shawe-Taylor, Nello Cristianini
      Pages 263-273
    6. Generalization Performance of Classifiers in Terms of Observed Covering Numbers
      John Shawe-Taylor, Robert C. Williamson
      Pages 274-285
    7. Entropy Numbers, Operators and Support Vector Kernels
      Robert C. Williamson, Alex J. Smola, Bernhard Schölkopf
      Pages 285-299
  10. Back Matter
    Pages 301-301
    PDF

About these proceedings

Keywords

Algorithmic Learning Computational Learning Inductive Inference Online Learning learning learning theory pattern recognition reinforcement learning

Editors and affiliations

  • Paul Fischer
    • 1
  • Hans Ulrich Simon
    • 2
  1. 1.Lehrstuhl für Informatik IIUniversität DortmundDortmundGermany
  2. 2.Fakultät für MathematikRuhr Universität BochumBochumGermany

Bibliographic information

  • DOI https://doi.org/10.1007/3-540-49097-3
  • Copyright Information Springer-Verlag Berlin Heidelberg 1999
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-540-65701-9
  • Online ISBN 978-3-540-49097-5
  • Series Print ISSN 0302-9743
  • Buy this book on publisher's site
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