Convexity and Concentration
This volume presents some of the research topics discussed at the 2014-2015 Annual Thematic Program Discrete Structures: Analysis and Applications at the Institute of Mathematics and its Applications during the Spring 2015 where geometric analysis, convex geometry and concentration phenomena were th...
Corporate Author: | |
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Other Authors: | , , |
Language: | English |
Published: |
New York, NY :
Springer New York : Imprint: Springer,
2017.
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Edition: | 1st ed. 2017. |
Series: | The IMA Volumes in Mathematics and its Applications,
161 |
Subjects: | |
Online Access: | https://doi.org/10.1007/978-1-4939-7005-6 |
Table of Contents:
- Part I: Probability and Concentration
- Interpolation of Probability Measures on Graphs
- Entropy and Thinning of Discrete Random Variables
- Structured Random Matrices
- Rates of Convergence for Empirical Spectral Measures: A Soft Approach
- Concentration of MEasure without Independence: A Unified Approach via the Martingale Method
- Strong Data-Processing Inequalities for Channels and Bayesian Networks
- An Application of a Functional Inequality to Quasi Invariance in Infinite Dimensions
- Borell's Formula on a Riemannian Manifold and Applications
- Fourth Moments and Products: Unified Estimates
- Asymptotic Expansions for Products of Characteristic Functions Under Moment Assumptions of non-Integer Orders
- Part II: Convexity and Concentration for Sets and Functions
- Non-Standard Constructions in Convex Geometry: Geometric Means of Convex Bodies
- Randomized Isoperimetric Inequalities
- Forward and Reverse Entropy Power Inequalities in Convex Geometry
- Log-Concave Functions
- On Some Problems Concerning Log-Concave Random Vectors
- Stability Results for Some Geometric Inequalities and their Functional Versions
- Measures of Sections of Convex Bodies
- On Isoperimetric Functions of Probability Measures Having Log-Concave Densities with Respect to the Standard Normal Law
- Counting Integer Points in Higher-Dimensional Polytopes
- The Chain Rule Operator Equation for Polynomials and Entire Functions.