Concentration of measure and generalized product of random vectors with an application to Hanson-Wright-like inequalities
(2102.08020)Abstract
Starting from concentration of measure hypotheses on $m$ random vectors $Z1,\ldots, Zm$, this article provides an expression of the concentration of functionals $\phi(Z1,\ldots, Zm)$ where the variations of $\phi$ on each variable depend on the product of the norms (or semi-norms) of the other variables (as if $\phi$ were a product). We illustrate the importance of this result through various generalizations of the Hanson-Wright concentration inequality as well as through a study of the random matrix $XDXT$ and its resolvent $Q = (I_p - \frac{1}{n}XDXT){-1}$, where $X$ and $D$ are random, which have fundamental interest in statistical machine learning applications.
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