Randomized Algorithms

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Cambridge University Press, Aug 25, 1995 - Computers - 476 pages
4 Reviews
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.
 

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Contents

I
ix
II
1
III
3
IV
28
V
43
VI
67
VII
101
VIII
127
X
195
XI
197
XII
234
XIII
278
XIV
306
XV
335
XVI
368
XVII
392

IX
161

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Popular passages

Page 463 - JP Schmidt, A. Siegel, and A. Srinivasan. Chernoff-Hoeffding bounds for applications with limited independence. In Proceedings of the 4th Annual ACM-SIAM Symposium on Discrete Algorithms, pages 331-340, 1993.
Page 451 - U. Manber and G. Myers. Suffix arrays: A new method for on-line string searches. In Proceedings of the 1st Annual ACM-SIAM Symposium on Discrete Algorithms, pages 319-327, 1990.
Page 452 - KL Clarkson. A Las Vegas algorithm for linear programming when the dimension is small. In Proc. 29th Annu. IEEE Sympos. Found. Comput. Sei., pages 452-456, 1988. [21] KL Clarkson and PW Shor. Applications of random sampling in computational geometry, II.

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About the author (1995)

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Dr Prabhakar Raghavan is Head of Yahoo! Research and a Consulting Professor of Computer Science at Stanford University.

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