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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
High-Dimensional Probability: An Introduction with Applications in Data Science

High-Dimensional Probability: An Introduction with Applications in Data Science

Vershynin, Roman

Hardcover

Series: Cambridge Statistical and Probabilistic Mathematics

Probability & Statistics

ISBN10: 1009490648
ISBN13: 9781009490641
Publisher: Cambridge University Press
Published: Feb 19 2026
Pages: 346
Weight: 1.80
Height: 0.81 Width: 7.00 Depth: 10.00
Language: English
'High-Dimensional Probability, ' winner of the 2019 PROSE Award in Mathematics, offers an accessible and friendly introduction to key probabilistic methods for mathematical data scientists. Streamlined and updated, this second edition integrates theory, core tools, and modern applications. Concentration inequalities are central, including classical results like Hoeffding's and Chernoff's inequalities, and modern ones like the matrix Bernstein inequality. The book also develops methods based on stochastic processes - Slepian's, Sudakov's, and Dudley's inequalities, generic chaining, and VC-based bounds. Applications include covariance estimation, clustering, networks, semidefinite programming, coding, dimension reduction, matrix completion, and machine learning. New to this edition are 200 additional exercises, alongside extra hints to assist with self-study. Material on analysis, probability, and linear algebra has been reworked and expanded to help bridge the gap from a typical undergraduate background to a second course in probability.

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