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Probability and Computing

Randomization and Probabilistic Techniques in Algorithms and Data Analysis

Michael Mitzenmacher, Eli Upfal

Cambridge University Press
Publication date : 2017-07-03

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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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About the book

Author

Michael Mitzenmacher , Eli Upfal

Imprint

Cambridge University Press

Collection

n.c

Publication date

2017-07-03

Pages

n.c

Print ISBN

9781107154889

Language

English

Ebook informations

EAN PDF

9781108110723

Price

£54.86

Copy count 0

Print count 0

File size 12216 Ko

Informations accessibility

EAN EPUB

9781108105958

Price

£54.86

Copy count 0

Print count 0

File size 79954 Ko

Informations accessibility

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About author(s)

Michael Mitzenmacher

Eli Upfal

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