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 for any . The bounds are based on -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 -statistics as well as for classes of symmetric functions via polynomial approximations on the sphere (Edgeworth-type expansions).
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