Probability and Computing: Randomized Algorithms and Probabilistic Analysis

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9780521835404: Probability and Computing: Randomized Algorithms and Probabilistic Analysis

Assuming only an elementary background in discrete mathematics, this textbook is an excellent introduction to the probabilistic techniques and paradigms used in the development of probabilistic algorithms and analyses. It includes random sampling, expectations, Markov's and Chevyshev's inequalities, Chernoff bounds, balls and bins models, the probabilistic method, Markov chains, MCMC, martingales, entropy, and other topics. The book is designed to accompany a one- or two-semester course for graduate students in computer science and applied mathematics.

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Book 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.Assuming only an elementary background in discrete mathematics, this 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, including random sampling, expectations, Markov's and Chevyshev's inequalities, Chernoff bounds, balls and bins models, the probabilistic method, Markov chains, MCMC, martingales, entropy, and other topics.

About the Author:

Michael Miztenmacher is a John L. Loeb Associate Professor in Computer Science at Harvard University. Having written nearly 100 articles on a variety of topics in computer science, his research focuses on randomized algorithms and networks. He has received an NSF CAREER Award and an Alfred P. Sloan Research Fellowship. In 2002, he shared the IEEE Information Theory Society Best Paper Award for his work on error-correcting codes.

Eli Upfal is Professor and Chair of Computer Science at Brown University. He has published more than 100 papers in refereed journals and professional conferences, and is the inventor of more than ten patents. His main research interests are randomized computation and probabilistic analysis of algorithms, with applications to optimization algorithms, communication networks, parallel and distributed computing and computational biology.

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Mitzenmacher, Michael; Upfal, Eli
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Book Description Cambridge University Press 2005-01-31, 2005. Book Condition: New. Brand new book, sourced directly from publisher. Dispatch time is 24-48 hours from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely. Bookseller Inventory # NU-LBR-00839439

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Book Description CAMBRIDGE UNIVERSITY PRESS, United Kingdom, 2005. Hardback. Book Condition: New. 258 x 178 mm. Language: English . Brand New Book. 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. Bookseller Inventory # LIB9780521835404

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Book Description CAMBRIDGE UNIVERSITY PRESS, United Kingdom, 2005. Hardback. Book Condition: New. 258 x 178 mm. Language: English . Brand New Book. 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. Bookseller Inventory # LIB9780521835404

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Book Description Cambridge University Press. Hardback. Book Condition: new. BRAND NEW, Probability and Computing: Randomized Algorithms and Probabilistic Analysis, Michael Mitzenmacher, Eli Upfal, 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. Bookseller Inventory # B9780521835404

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Book Description Cambridge University Press, 2005. Book Condition: New. 2005. Hardcover. An excellent 2005 introduction to the probabilistic techniques and paradigms used in the development of probabilistic algorithms and analyses. Num Pages: 370 pages, 50 b/w illus. 80 exercises. BIC Classification: PBKS; UYA. Category: (P) Professional & Vocational; (U) Tertiary Education (US: College). Dimension: 260 x 187 x 15. Weight in Grams: 872. . . . . . . Bookseller Inventory # V9780521835404

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Book Description Cambridge University Press, 2005. Hardcover. Book Condition: New. Brand New Book. Shipping: Once your order has been confirmed and payment received, your order will then be processed. The book will be located by our staff, packaged and despatched to you as quickly as possible. From time to time, items get mislaid en route. If your item fails to arrive, please contact us first. We will endeavour to trace the item for you and where necessary, replace or refund the item. Please do not leave negative feedback without contacting us first. All orders will be dispatched within two working days. If you have any quesions please contact us. Bookseller Inventory # V9780521835404

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Book Description Cambridge University Press. Book Condition: New. 2005. Hardcover. An excellent 2005 introduction to the probabilistic techniques and paradigms used in the development of probabilistic algorithms and analyses. Num Pages: 370 pages, 50 b/w illus. 80 exercises. BIC Classification: PBKS; UYA. Category: (P) Professional & Vocational; (U) Tertiary Education (US: College). Dimension: 260 x 187 x 15. Weight in Grams: 872. . . . . . Books ship from the US and Ireland. Bookseller Inventory # V9780521835404

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