Probability and Computing
Randomization and Probabilistic Techniques in Algorithms and Data Analysis
By Michael Mitzenmacher,Eli Upfal | Publisher: Cambridge University Press
About the book
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.
Editions of Probability and Computing
- Hardcover
- ISBN 9781107154889
Read an Excerpt
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.
Frequently Asked Questions
What is Probability and Computing about?
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.
What core themes, tropes, or subjects are explored in Probability and Computing?
Computing and Information Technology > Computer programming / software engineering > Algorithms and data structures
Where can I read a sample of Probability and Computing?
You can read an official preview of the few pages here https://www.book2look.com/book/9781107154889
Who is/are the Author/s of the book Probability and Computing?
Michael Mitzenmacher,Eli Upfal
What are the ISBN numbers for the physical and digital editions?
Probability and Computing is available as hardcover(ISBN 9781107154889)