High-Dimensional Probability: An Introduction with Applications in Data Science (Cambridge Series in Statistical and Probabilistic Mathematics)

Synopsis

Preliminaries On Random Variables -- Concentration Of Sums Of Independent Random Variables -- Random Vectors In High Dimensions -- Random Matrices -- Concentration Without Independence -- Quadratic Forms, Symmetrization And Contraction -- Random Processes -- Chaining -- Deviations Of Random Matrices And Geometric Consequences -- Sparse Recovery -- Dvoretzky-milman's Theorem. Roman Vershynin. Includes Bibliographical References And Index.