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Probability and Computing: Randomization and Probabilistic Techniques in Algorithms and Data Analysis
Upfal Mitzenmacher
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Description for Probability and Computing: Randomization and Probabilistic Techniques in Algorithms and Data Analysis
hardcover. This greatly expanded new edition offers a comprehensive introduction to randomization and probabilistic techniques in modern computer science. Num Pages: 488 pages, 8 b/w illus. 1 table. BIC Classification: PBT; UMB. Category: (U) Tertiary Education (US: College). Dimension: 253 x 177. .
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 ... Read more
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 ... Read more
Product Details
Format
Hardback
Publication date
2017
Publisher
Cambridge University Press
Condition
New
Number of Pages
484
Place of Publication
Cambridge, United Kingdom
ISBN
9781107154889
SKU
9781107154889
Shipping Time
Usually ships in 2 to 4 working days
Ref
99-1
About Upfal Mitzenmacher
Michael Mitzenmacher is a Professor of Computer Science in the School of Engineering and Applied Sciences at Harvard University, Massachusetts. Professor Mitzenmacher has authored or co-authored over 200 conference and journal publications on a variety of topics, including algorithms for the internet, efficient hash-based data structures, erasure and error-correcting codes, power laws, and compression. His work on low-density parity-check codes ... Read more
Reviews for Probability and Computing: Randomization and Probabilistic Techniques in Algorithms and Data Analysis
'As randomized methods continue to grow in importance, this textbook provides a rigorous yet accessible introduction to fundamental concepts that need to be widely known. The new chapters in this second edition, about sample size and power laws, make it especially valuable for today's applications.' Donald E. Knuth, Stanford University, California 'Of all the courses I have taught at Berkeley, ... Read more