Probability and computing : Randomization and probabilistic techniques in algorithms and data analysis/ Michael Mitzenmacher, Eli Upfal.
Publication details: New York: Cambridge University Press, 2017.Edition: 2nd edDescription: 467 pISBN:- 9781107154889
- 518.1 Q7
Item type | Current library | Call number | Status | Date due | Barcode | Item holds |
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Books | Mahatma Gandhi University Library General Stacks | 518.1 Q7 (Browse shelf(Opens below)) | Available | 59431 |
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518.028 5 Q5 Accelerating MATLAB performance: | 518.028 5 Q51 Essential MATLAB and Octave / | 518.1 Q5 Design and analysis of algorithms/ | 518.1 Q7 Probability and computing | 518.1 R2 A guide to grapgh algorithms/ | 518.282 R0 An introduction to sequential Monte Carlo/ | 519 P7 Probability and statistics/ |
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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