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Probability and Computing: Randomization and Probabilistic Techniques in Algorithms and Data Analysis
Michael Mitzenmacher
(Author)
·
Eli Upfal
(Author)
·
Cambridge University Press
· Hardcover
Probability and Computing: Randomization and Probabilistic Techniques in Algorithms and Data Analysis - Mitzenmacher, Michael ; Upfal, Eli
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Synopsis "Probability and Computing: Randomization and Probabilistic Techniques in Algorithms and Data Analysis"
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.
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All books in our catalog are Original.
The book is written in English.
The binding of this edition is Hardcover.
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