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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EAN: 9781107154889
UPC: 9781107154889
ISBN: 9781107154889
MPN: N/A
Item Length: 25.4 cm
Item Height: 260 mm
Item Width: 182 mm
Author: Eli Upfal, Michael Mitzenmacher
Publication Name: Probability and Computing: Randomization and Probabilistic Techniques in Algorithms and Data Analysis
Format: Hardcover
Language: English
Publisher: Cambridge University Press
Subject: Computer Science, Mathematics
Publication Year: 2017
Type: Textbook
Item Weight: 1150 g
Number of Pages: 484 Pages
