Probability and Computing
Randomization and Probabilistic Techniques in Algorithms and Data Analysis
Published on 3. July 2017
978-1-108-10595-8 (ISBN)
Description
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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Additional editions
Michael Mitzenmacher | Eli Upfal
Probability and Computing
Randomization and Probabilistic Techniques in Algorithms and Data Analysis
Book
07/2017
2nd Edition
Cambridge University Press
€65.00
Available immediately
