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Randomized Algorithms / Edition 1
     

Randomized Algorithms / Edition 1

by Prabhakar Raghavan, Rajeev Motwani
 

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ISBN-10: 0521474655

ISBN-13: 9780521474658

Pub. Date: 08/28/1995

Publisher: Cambridge University Press

For many applications, a randomized algorithm is either the simplest or the fastest algorithm available, and sometimes both. This book introduces the basic concepts in the design and analysis of randomized algorithms. The first part of the text presents basic tools such as probability theory and probabilistic analysis that are frequently used in algorithmic

Overview

For many applications, a randomized algorithm is either the simplest or the fastest algorithm available, and sometimes both. This book introduces the basic concepts in the design and analysis of randomized algorithms. The first part of the text presents basic tools such as probability theory and probabilistic analysis that are frequently used in algorithmic applications. Algorithmic examples are also given to illustrate the use of each tool in a concrete setting. In the second part of the book, each chapter focuses on an important area to which randomized algorithms can be applied, providing a comprehensive and representative selection of the algorithms that might be used in each of these areas. Although written primarily as a text for advanced undergraduates and graduate students, this book should also prove invaluable as a reference for professionals and researchers.

Product Details

ISBN-13:
9780521474658
Publisher:
Cambridge University Press
Publication date:
08/28/1995
Edition description:
New Edition
Pages:
492
Product dimensions:
6.97(w) x 9.96(h) x 1.26(d)

Table of Contents

Part I. Tools and Techniques: 1. Introduction; 2. Game-theoretic techniques; 3. Moments and deviations; 4. Tail inequalities; 5. The probabilistic method; 6. Markov chains and random walks; 7. Algebraic techniques; Part II. Applications: 8. Data structures; 9. Geometric algorithms and linear programming; 10. Graph algorithms; 11. Approximate counting; 12. Parallel and distributed algorithms; 13. Online algorithms; 14. Number theory and algebra; Appendix A: notational index; Appendix B: mathematical background; Appendix C: basic probability theory.

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