High Dimensional Probability X

This volume collects selected papers from the Tenth High Dimensional Probability conference, held from June 12 to 16, 2023 in Bdlewo, Poland. These papers cover a wide range of topics and demonstrate how high-dimensional probability remains an active area of research with applications across many mathematical disciplines. Topics covered include:

• The Gram-Schmidt walk algorithm;
• Variance bounds;
• Random interlacements;

• Contraction theorems on the half-space.
  High Dimensional Probability X will be a valuable resource for researchers in this area.

  Demonstrates how high-dimensional probability remains an active area of research with applications to many disciplines Shows a variety of useful interactions and applications with other mathematical fields Collects selected papers from the Tenth High Dimensional Probability conference, held from June 12-16, 2023

  Inhalt

Chapter 1 Optimal constants in concentration inequalities on the sphere and in the Gauss space.- Chapter 2 Some remarks on the Gram-Schmidt walk algorithm and consequences for Komlos conjecture.- Chapter 3 Some notes on moment inequalities for heavy-tailed distributions.- Chapter 4 Stability of Klartag's improved Lichnerowicz inequality.- Chapter 5 Variance bounds: some old and some new.- Chapter 6 Some obstructions to contraction theorems on the half-sphere.- Chapter 7 Dimension-free comparison estimates for suprema of some canonical processes.- Chapter 8 Sharp phase transitions in Euclidean integral geometry.- Chapter 9 Fourier analytic bounds for Zolotarev distances, and applications to empirical measures.- Chapter 10 A note on the fluctuations of the resolvent traces of a tensor model of sample covariance matrices.- Chapter 11 New Berry-Esseen bounds for random sums of centered random variables.- Chapter 12 The large and moderate deviations approach in geometric functional.- Chapter 13 Random interlacements: the discontinuous case.- Chapter 14 Local moduli of continuity for permanental processes that are zero at zero.- Chapter 15 Estimation of trace functionals and spectral measures of covariance operators in Gaussian models.- Chapter 16 Higher-order perturbation expansions for eigenvalues and eigenprojections I: simple eigenvalues and random perturbations.