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Discrete Probability and Algorithms

  • Conference proceedings
  • © 1995

Overview

Editors:
  1. David Aldous

    1. Department of Statistics, University of California, Berkeley, USA

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  2. Persi Diaconis

    1. Department of Mathematics, Harvard University, Cambridge, USA

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  3. Joel Spencer

    1. Department of Computer Science Courant Institute, New York University, New York, USA

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  4. J. Michael Steele

    1. Department of Statistics, The Wharton School University of Pennsylvania, Philadelphia, USA

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Part of the book series: The IMA Volumes in Mathematics and its Applications (IMA, volume 72)

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Table of contents (11 papers)

  1. Front Matter

    Pages i-xvii
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  2. On Simulating a Markov Chain Stationary Distribution when Transition Probabilities are Unknown

    • David Aldous
    Pages 1-9

  3. A Note on Network Reliability

    • Noga Alon
    Pages 11-14

  4. Rectangular Arrays with Fixed Margins

    • Persi Diaconis, Anil Gangolli
    Pages 15-41

  5. Three Examples of Monte-Carlo Markov Chains: At the Interface Between Statistical Computing, Computer Science, and Statistical Mechanics

    • Persi Diaconis, Susan Holmes
    Pages 43-56

  6. The Move-To-Front Rule for Self-Organizing Lists with Markov Dependent Requests

    • Robert P. Dobrow, James Allen Fill
    Pages 57-80

  7. The Asymptotic Lower Bound on the Diagonal Ramsey Numbers: A Closer Look

    • Anant P. Godbole, Daphne E. Skipper, Rachel A. Sunley
    Pages 81-94

  8. Random Walks and Undirected Graph Connectivity: A Survey

    • Anna R. Karlin, Prabhakar Raghavan
    Pages 95-101

  9. Sidon Sets with Small Gaps

    • Joel Spencer, Prasad Tetali
    Pages 103-109

  10. Variations on the Monotone Subsequence Theme of Erdös and Szekeres

    • J. Michael Steele
    Pages 111-131

  11. Randomised Approximation Schemes for Tutte-Gröthendieck Invariants

    • Dominic Welsh
    Pages 133-148

  12. Quasi-Additive Euclidean Functionals

    • J. E. Yukich
    Pages 149-158
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Keywords

About this book

Discrete probability theory and the theory of algorithms have become close partners over the last ten years, though the roots of this partnership go back much longer. The papers in this volume address the latest developments in this active field. They are from the IMA Workshops "Probability and Algorithms" and "The Finite Markov Chain Renaissance." They represent the current thinking of many of the world's leading experts in the field.

Researchers and graduate students in probability, computer science, combinatorics, and optimization theory will all be interested in this collection of articles. The techniques developed and surveyed in this volume are still undergoing rapid development, and many of the articles of the collection offer an expositionally pleasant entree into a research area of growing importance.

Editors and Affiliations

  • Department of Statistics, University of California, Berkeley, USA

    David Aldous

  • Department of Mathematics, Harvard University, Cambridge, USA

    Persi Diaconis

  • Department of Computer Science Courant Institute, New York University, New York, USA

    Joel Spencer

  • Department of Statistics, The Wharton School University of Pennsylvania, Philadelphia, USA

    J. Michael Steele

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