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Chevet-type inequalities for subexponential Weibull variables and estimates for norms of random matrices

Published 8 Sep 2023 in math.PR and math.FA | (2309.04214v2)

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.

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