English

Variance estimates and almost Euclidean structure

Functional Analysis 2017-10-23 v2

Abstract

We introduce and initiate the study of new parameters associated with any norm and any log-concave measure on Rn\mathbb R^n, which provide sharp distributional inequalities. In the Gaussian context this investigation sheds light to the importance of the statistical measures of dispersion of the norm in connection with the local structure of the ambient space. As a byproduct of our study, we provide a short proof of Dvoretzky's theorem which not only supports the aforementioned significance but also complements the classical probabilistic formulation.

Keywords

Cite

@article{arxiv.1703.10244,
  title  = {Variance estimates and almost Euclidean structure},
  author = {Grigoris Paouris and Petros Valettas},
  journal= {arXiv preprint arXiv:1703.10244},
  year   = {2017}
}

Comments

minor revision; to appear in Adv. Geom

R2 v1 2026-06-22T19:01:41.544Z