Michael Mitzenmacher,Eli Upfal: Probability and Computing: Randomized Algorithms and Probabilistic Analysis

Probability and Computing: Randomized Algorithms and Probabilistic Analysis


Description

Randomization and probabilistic techniques play an important role in modern computer science, with applications ranging from combinatorial optimization and machine learning to communication networks and secure protocols. This 2005 textbook is designed to accompany a one- or two-semester course for advanced undergraduates or beginning graduate students in computer science and applied mathematics. It gives an excellent introduction to the probabilistic techniques and paradigms used in the development of probabilistic algorithms and analyses. It assumes only an elementary background in discrete mathematics and gives a rigorous yet accessible treatment of the material, with numerous examples and applications. The first half of the book covers core material, including random sampling, expectations, Markov's inequality, Chevyshev's inequality, Chernoff bounds, the probabilistic method and Markov chains. The second half covers more advanced topics such as continuous probability, applications of limited independence, entropy, Markov chain Monte Carlo methods and balanced allocations. With its comprehensive selection of topics, along with many examples and exercises, this book is an indispensable teaching tool.


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Author: Michael Mitzenmacher,Eli Upfal
Number of Pages: 370 pages
Published Date: 15 Nov 2005
Publisher: CAMBRIDGE UNIVERSITY PRESS
Publication Country: Cambridge, United Kingdom
Language: English
ISBN: 9780521835404
Download Link: Click Here
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