Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
144 tokens/sec
GPT-4o
7 tokens/sec
Gemini 2.5 Pro Pro
46 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
38 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Chevet-type inequalities for subexponential Weibull variables and estimates for norms of random matrices (2309.04214v2)

Published 8 Sep 2023 in math.PR and math.FA

Abstract: We prove two-sided Chevet-type inequalities for independent symmetric Weibull random variables with shape parameter $r\in[1,2]$. We apply them to provide two-sided estimates for operator norms from $\ell_pn$ to $\ell_qm$ of random matrices $(a_ib_jX_{i,j}){i\le m, j\le n}$, in the case when $X{i,j}$'s are iid symmetric Weibull variables with shape parameter $r\in[1,2]$ or when $X$ is an isotropic log-concave unconditional random matrix. We also show how these Chevet-type inequalities imply two-sided bounds for maximal norms from $\ell_pn$ to $\ell_qm$ of submatrices of $X$ in both Weibull and log-concave settings.

Citations (1)

Summary

We haven't generated a summary for this paper yet.