Probability and Computing : Randomization and Probabilistic Techniques in Algorithms and Data Analysis
Language: English
Published by Cambridge University Pr. Jan 2017, 2017
- Hardcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
Condition: New
£ 74.26
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Add to basketItem description from seller
Neuware - Greatly expanded, this new edition requires only an elementary background in discrete mathematics and offers a comprehensive introduction to the role of randomization and probabilistic techniques in modern computer science. Newly added chapters and sections cover topics including normal distributions, sample complexity, VC dimension, Rademacher complexity, power laws and related distributions, cuckoo hashing, and the Lovasz Local Lemma. Material relevant to machine learning and big data analysis enables students to learn modern techniques and applications. Among the many new exercises and examples are programming-related exercises that provide students with excellent training in solving relevant problems. This book provides an indispensable teaching tool to accompany a one- or two-semester course for advanced undergraduate students in computer science and applied mathematics.
Seller Inventory # 9781107154889
- Title
- Probability and Computing : Randomization and Probabilistic Techniques in Algorithms and Data Analysis
- Author
- Michael Mitzenmacher
- Publisher
- Cambridge University Pr. Jan 2017
- Publication year
- 2017
- Condition
- Neu
- Binding
- Buch
- Language
- English
- ISBN 10
- 110715488X
- ISBN 13
- 9781107154889
- Edition
- 2nd Edition
- Item weight
- 1,158 grams
- Dimensions
- 259x182x27 mm
"Synopsis" may belong to another edition of this title.
About the Author
Eli Upfal is a Professor of Computer Science at Brown University, where he was also the department chair from 2002 to 2007. Prior to joining Brown in 1998, he was a researcher and project manager at the IBM Almaden Research Center, and a professor at the Weizmann Institute of Science, Israel. His main research interests are randomized algorithms, probabilistic analysis of algorithms, and computational statistics, with applications ranging from combinatorial and stochastic optimization, massive data analysis and sampling complexity to computational biology, and computational finance.
"About the title" may belong to another edition of this title.
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