Skip to main content
SpringerLink
Log in

Computational Learning Theory

4th European Conference, EuroCOLT'99 Nordkirchen, Germany, March 29-31, 1999 Proceedings

  • Conference proceedings
  • © 1999

Overview

Editors:
  1. Paul Fischer

    1. Lehrstuhl für Informatik II, Universität Dortmund, Dortmund, Germany

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  2. Hans Ulrich Simon

    1. Fakultät für Mathematik, Ruhr Universität Bochum, Bochum, Germany

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

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

Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)

Included in the following conference series:

Conference proceedings info: EuroCOLT 1999.

This is a preview of subscription content, log in via an institution to check access.

Access this book

Log in via an institution
eBook USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access

Licence this eBook for your library

Institutional subscriptions

Table of contents (23 papers)

  1. Front Matter

    Pages I-X
    Download chapter 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

  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
Back to top

Keywords

Editors and Affiliations

  • Lehrstuhl für Informatik II, Universität Dortmund, Dortmund, Germany

    Paul Fischer

  • Fakultät für Mathematik, Ruhr Universität Bochum, Bochum, Germany

    Hans Ulrich Simon

Bibliographic Information

Publish with us

Policies and ethics

Back to top

Search

Navigation