Titlebook: Concentration and Gaussian Approximation for Randomized Sums; Sergey Bobkov,Gennadiy Chistyakov,Friedrich G?tze Book 2023 The Editor(s) (i

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書目名稱Concentration and Gaussian Approximation for Randomized Sums影響因子(影響力)




書目名稱Concentration and Gaussian Approximation for Randomized Sums影響因子(影響力)學科排名




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書目名稱Concentration and Gaussian Approximation for Randomized Sums網絡公開度學科排名




書目名稱Concentration and Gaussian Approximation for Randomized Sums被引頻次




書目名稱Concentration and Gaussian Approximation for Randomized Sums被引頻次學科排名




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書目名稱Concentration and Gaussian Approximation for Randomized Sums年度引用學科排名




書目名稱Concentration and Gaussian Approximation for Randomized Sums讀者反饋




書目名稱Concentration and Gaussian Approximation for Randomized Sums讀者反饋學科排名

Opponent

Book 2023and results from probability and analysis which are needed for the remainder of the book, the latter parts provide a thorough exposition of concentration, analysis on the sphere, higher order normal approximation and classes of weighted sums of dependent random variables with and without symmetries.

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OVERT

Book 2023es. The central topics of the book are weighted sums of random variables and the concentration of their distributions around Gaussian laws. The analysis takes place within the broader context of concentration of measure for functions on high-dimensional spheres. Starting from the usual concentration

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Logarithmic Sobolev Inequalitiesies of the involved entropy functional and then describe several important examples of measures satisfying logarithmic Sobolev inequalities. The remaining part of the chapter deals with various bounds that are valid in the presence of logarithmic Sobolev inequalities.

劇本

Slow coherency and weak connections, chapter, we describe general tools in the form of smoothing and Berry–Esseen-type inequalities, which allow one to perform the transition from the results about closeness or smallness of Fourier–Stieltjes transforms to corresponding results about the associated functions of bounded variation.

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2199-3130 ons around Gaussian laws.Contains a detailed exposition of t.This book describes extensions of Sudakov‘s classical result on the concentration of measure phenomenon for weighted sums of dependent random variables. The central topics of the book are weighted sums of random variables and the concentra

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Slow coherency and weak connections,ll” probabilities), for joint distributions of pairwise independent random variables, and for coordinate-symmetric distributions. We also discuss the class of logarithmically concave measures and include some additional background material which will be needed later on.