For many applications, a randomized algorithm is either the simplest or the fastest algorithm available, and sometimes both. This book introduces the basic. Randomized Algorithms eBook: Rajeev Motwani, Prabhakar Raghavan: site. in: site Store. Motwani, Rajeev. Randomized ·algorithms / Rajeev Motwani, Prabhakar Raghavan. p. em. Includes bibliographical references and index. .SBN
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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. download Randomized Algorithms on abromishico.cf ✓ FREE SHIPPING on qualified orders. Editorial Reviews. Review. "The techniques described by Rajeev Motwani and Prabhaker Advanced Search · site Store · site eBooks · Science & Math.
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.
User Review - Flag as inappropriate I am getting so frustrated after reading this book, only mathematical intuitions are given and explain in a very bad manner. User Review - Flag as inappropriate hacked. Selected pages Title Page.
Table of Contents. Contents I. Siegel, and A.
Chernoff-Hoeffding bounds for applications with limited independence. Page - U. Manber and G.
Suffix arrays: A new method for on-line string searches. Page - KL Clarkson. A Las Vegas algorithm for linear programming when the dimension is small. For many applications a randomized algorithm is the simplest algorithm available, or the fastest, or both. This book presents basic tools from probability theory used in algorithmic applications, with examples to illustrate the use of each tool in a concrete setting.
Several important areas of application of randomized algorithms are explored in detail, giving a representa For many applications a randomized algorithm is the simplest algorithm available, or the fastest, or both.
Several important areas of application of randomized algorithms are explored in detail, giving a representative selection of the algorithms in these areas. Although written primarily as a text, this book should also prove invaluable as a reference for professionals and researchers.
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Hardcover , pages. Published August 1st by Cambridge University Press.
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Sort order. Feb 23, Mugizi Rwebangira rated it really liked it.
Best I've seen. Jan 10, Nick Black rated it really liked it.
site Clearly regarded as the standard in this field new to me this semester , with apparently a heavier emphasis on continuous probabilities and thus requirements of measure theory, Borel algebras, and the Lesbesgue integral, knowledge of which is unfortunately no longer a safe assumption regarding CS grad students than our text.
Oct 21, Zarathustra Goertzel rated it liked it. Basically read and worked through the first part for class, and then the chapters leading up to hashing and treaps.
The hashing chapter was a bit awkward and inelegant. The one on treaps was quite beautiful. Chapter 4 on the Chernoff bound and random parallel hypercube routing was fun, and well complemented by chapter 5 on the probabilistic method.
So, 'tis a good intro ;-. Apr 17, dead letter office rated it it was ok Shelves: Apr 02, DJ marked it as to-read Shelves: Nice book on randomized algorithms recommended by Nielsen and chuang, but as Nick mentions, the maths required are still one grad analysis class beyond me. Kira rated it it was amazing Apr 07, David Li rated it really liked it Feb 24, A rated it really liked it Oct 14, Bo Brinkman rated it it was amazing Apr 01, David Liao rated it it was amazing Jul 20, Made Easy..
Modeling and Reasoning with Bayesian Networks.
Kengo Nakajima. A comprehensive and representative selection of the algorithms in these areas is also given.
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