Discrete Probability and Algorithms

by David Aldous (Editor), Persi Diaconis (Editor), Joel Spencer (Editor), J. Michael Steele (Editor)

Overview

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.

Product Details

ISBN-13:	9781461269052
Publisher:	Springer New York
Publication date:	09/28/2012
Series:	The IMA Volumes in Mathematics and its Applications , #72
Edition description:	Softcover reprint of the original 1st ed. 1995
Pages:	158
Product dimensions:	6.10(w) x 9.25(h) x 0.01(d)

Table of Contents

On simulating a Markov chain stationary distribution when transition probabilities are unknown.- A note on network reliability.- Rectangular arrays with fixed margins.- Three examples of Monte-Carlo Markov chains: at the interface between statistical computing, computer science, and statistical mechanics.- The move-to-front rule for self-organizing lists with Markov dependent requests.- The asymptotic lower bound on the diagonal Ramsey numbers: A closer look.- Random walks and undirected graph connectivity: A survey.- Sidon sets with small gaps.- Variations on the monotone subsequence theme of Erdős and Szekeres.- Randomised approximation schemes for Tutte-Gröthendieck invariants.- Quasi-additive Euclidean functionals.