Probability and computing : randomization and probabilistic techniques in algorithms and data analysis

By:

Mitzenmacher, Michael

Contributor(s):

Upfal, Eli

Material type: Text

9781107154889

Subject(s):

DDC classification:

518.1 MIT-P

LOC classification:

QA274 .M574 2017

Online resources:

Summary: "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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Holdings
Item type	Current library	Collection	Call number	Status	Date due	Barcode	Item holds	Course reserves
Books	IIITD Reference	Mathematics	REF 518.1 MIT-P (Browse shelf(Opens below))	Not for loan		011142		Randomized Algorithms UG/PG WNT24

Total holds: 0

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This book includes bibliographical references and index.

"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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