English

Higher Order Concentration of Measure

Probability 2018-08-14 v2

Abstract

We study sharpened forms of the concentration of measure phenomenon typically centered at stochastic expansions of order d1d-1 for any dNd \in \mathbb{N}. The bounds are based on dd-th order derivatives or difference operators. In particular, we consider deviations of functions of independent random variables and differentiable functions over probability measures satisfying a logarithmic Sobolev inequality, and functions on the unit sphere. Applications include concentration inequalities for UU-statistics as well as for classes of symmetric functions via polynomial approximations on the sphere (Edgeworth-type expansions).

Keywords

Cite

@article{arxiv.1709.06838,
  title  = {Higher Order Concentration of Measure},
  author = {Sergey G. Bobkov and Friedrich Götze and Holger Sambale},
  journal= {arXiv preprint arXiv:1709.06838},
  year   = {2018}
}

Comments

some new material and examples added

R2 v1 2026-06-22T21:49:19.582Z