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KuTenk 2000 - BMST293806-Probability and Computing Randomized Algorithms and Probabilistic Analysis

by Michael Mitzenmacher and Eli Upfal

2005 (368 pages)

ISBN:0521835402

With its comprehensive selection of topics, and many examples and exercises, this book gives an excellent introduction to the probabilistic techniques and paradigms used in the development of probabilistic algorithms and analyses.

Table of Contents

Probability and Computing—Randomized Algorithms and Probabilistic Analysis
Preface
Chapter One	-	Events and Probability
Chapter Two	-	Discrete Random Variables and Expectation
Chapter Three	-	Moments and Deviations
Chapter Four	-	Chernoff Bounds
Chapter Five	-	Balls, Bins, and Random Graphs
Chapter Six	-	The Probabilistic Method
Chapter Seven	-	Markov Chains and Random Walks
Chapter Eight	-	Continuous Distributions and the Poisson Process
Chapter Nine	-	Entropy, Randomness, and Information
Chapter Ten	-	The Monte Carlo Method
Chapter Eleven	-	Coupling of Markov Chains
Chapter Twelve	-	Martingales
Chapter Thirteen	-	Pairwise Independence and Universal Hash Functions
Chapter Fourteen	-	Balanced Allocations
Further Reading