Skip to main content
Springer Nature Link
Log in
Image

Computational Learning Theory

14th Annual Conference on Computational Learning Theory, COLT 2001 and 5th European Conference on Computational Learning Theory, EuroCOLT 2001, Amsterdam, The Netherlands, July 16-19, 2001, Proceedings

  • Conference proceedings
  • © 2001
Save conference proceedings
View saved research

Overview

Editors:
  1. David Helmbold

    1. School of Engineering, Department of Computer Science, University of California, Santa Cruz, Santa Cruz, USA

  2. Bob Williamson

    1. Research School of Information Sciences and Engineering Department of Telecommunications Engineering, Australian National University, Canberra, Australia

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 2111)

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

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

Access this book

Log in via an institution

Other ways to access

Licence this eBook for your library

Institutional subscriptions

Explore related subjects

Discover the latest articles, books and news in related subjects.

Table of contents (41 papers)

  1. Front Matter

    Pages I-IX
    Download chapter PDF

  2. How Many Queries Are Needed to Learn One Bit of Information?

    • Hans Ulrich Simon
    Pages 1-13

  3. Radial Basis Function Neural Networks Have Superlinear VC Dimension

    • Michael Schmitt
    Pages 14-30

  4. Tracking a Small Set of Experts by Mixing Past Posteriors

    • Olivier Bousquet, Manfred K. Warmuth
    Pages 31-47

  5. Potential-Based Algorithms in Online Prediction and Game Theory

    • Nicolò Cesa-Bianchi, Gábor Lugosi
    Pages 48-64

  6. A Sequential Approximation Bound for Some Sample-Dependent Convex Optimization Problems with Applications in Learning

    • Tong Zhang
    Pages 65-81

  7. Efficiently Approximating Weighted Sums with Exponentially Many Terms

    • Deepak Chawla, Lin Li, Stephen Scott
    Pages 82-98

  8. Ultraconservative Online Algorithms for Multiclass Problems

    • Koby Crammer, Yoram Singer
    Pages 99-115

  9. Estimating a Boolean Perceptron from Its Average Satisfying Assignment: A Bound on the Precision Required

    • Paul W. Goldberg
    Pages 116-127

  10. Adaptive Strategies and Regret Minimization in Arbitrarily Varying Markov Environments

    • Shie Mannor, Nahum Shimkin
    Pages 128-142

  11. Robust Learning — Rich and Poor

    • John Case, Sanjay Jain, Frank Stephan, Rolf Wiehagen
    Pages 143-159

  12. On the Synthesis of Strategies Identifying Recursive Functions

    • Sandra Zilles
    Pages 160-176

  13. Intrinsic Complexity of Learning Geometrical Concepts from Positive Data

    • Sanjay Jain, Efim Kinber
    Pages 177-193

  14. Toward a Computational Theory of Data Acquisition and Truthing

    • David G. Stork
    Pages 194-207

  15. Discrete Prediction Games with Arbitrary Feedback and Loss (Extended Abstract)

    • Antonio Piccolboni, Christian Schindelhauer
    Pages 208-223

  16. Rademacher and Gaussian Complexities: Risk Bounds and Structural Results

    • Peter L. Bartlett, Shahar Mendelson
    Pages 224-240

  17. Further Explanation of the Effectiveness of Voting Methods: The Game between Margins and Weights

    • Vladimir Koltchinskii, Dmitriy Panchenko, Fernando Lozano
    Pages 241-255

  18. Geometric Methods in the Analysis of Glivenko-Cantelli Classes

    • Shahar Mendelson
    Pages 256-272

  19. Learning Relatively Small Classes

    • Shahar Mendelson
    Pages 273-288

  20. On Agnostic Learning with {0, *, 1}-Valued and Real-Valued Hypotheses

    • Philip M. Long
    Pages 289-302
Back to top

Editors and Affiliations

  • School of Engineering, Department of Computer Science, University of California, Santa Cruz, Santa Cruz, USA

    David Helmbold

  • Research School of Information Sciences and Engineering Department of Telecommunications Engineering, Australian National University, Canberra, Australia

    Bob Williamson

Accessibility Information

Accessibility information for this book is coming soon. We're working to make it available as quickly as possible. Thank you for your patience.

Bibliographic Information

Keywords

Publish with us

Policies and ethics

Back to top