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Randomized Algorithms

Randomized Algorithms

Randomized Algorithms

Rajeev Motwani, Stanford University, California
Prabhakar Raghavan, Google, Inc.
August 1995
Hardback
9780521474658
CAD$106.95
Hardback
USD
eBook

    For many applications a randomized algorithm is either the simplest algorithm available, or the fastest, or both. This tutorial presents the basic concepts in the design and analysis of randomized algorithms. The first part of the book presents tools from probability theory and probabilistic analysis that are recurrent in algorithmic applications. Algorithmic examples are given to illustrate the use of each tool in a concrete setting. In the second part of the book, each of the seven chapters focuses on one important area of application of randomized algorithms: data structures; geometric algorithms; graph algorithms; number theory; enumeration; parallel algorithms; and on-line algorithms. A comprehensive and representative selection of the algorithms in these areas is also given. This book should prove invaluable as a reference for researchers and professional programmers, as well as for students.

    • Only book currently published in the growing field of randomized algorithms
    • Topic has applications in computer science, operations research, mathematics and statistics
    • Practical and self-contained
    • Written by two well-known researchers in the field

    Reviews & endorsements

    "The techniques described by Rajeev Motwani and Prabhaker Raghavan are wide-ranging and powerful, so this book is an important one...We are particularly lucky, therefore, that this excellent volume does us so proud!...clearly written and well thought out, with an interesting collection of exercises and applications, and shows the comprehensive breadth and valuable insights of a mature text...I would recommend the book both to newcomers to the field and to more seasoned practitioners...It is a pleasure to read." John H. Halton, American Scientist

    "...the first comprehensive account of the current state of this burgeoning subject...Every aspect of this book...shows evidence of ample thoughtfulness...an essential acquisition..." D.V. Feldman, Choice

    "Randomization has come to be recognized as a fundamental tool for the construction of simple and efficient algorithms. Motwani and Raghavan provide an excellent overview of randomized techniques in algorithm construction, demonstrating their impact on virtually every domain in which computation is done. This book will surely exert a powerful influence on the way algorithm design is practiced and taught." Richard M. Karp

    "This is an authoritative work by researchers active in the field. The book is welcome as a reference work, as a source book for algorithmic ideas, and as a graduate-level course text....In the latter role, the book is greatly enhanced by the provision of numerous exercises scattered throughout the text (to test and deepen the reader's understanding), together with extensive selections of harder problems at the end of each chapter. The continued attention of seasoned researchers is assured by the inclusion of a number of open research problems. This is very much an active research area, and if newcomers are attracted into it through reading this book, then it will have served an additional useful purpose." Mark R. Jerrum, Mathematical Reviews

    "The book can serve as an excellent basis for a graduate course. It is also highly recommended for students and researchers who wish to deepen their knowledge of the subject." Y. Aumann, Computing Reviews

    "...carefully written, with exact definitions and complete proofs.... I believe that the book, with its vast coverage, will be an invaluable source for active researchers in the field." Y. Aumann, Theory of Computation

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    Product details

    September 2013
    Adobe eBook Reader
    9781139632409
    0 pages
    0kg
    This ISBN is for an eBook version which is distributed on our behalf by a third party.

    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.
    Resources for
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    Size: 39.07 KB
    Type: application/pdf