Strengthened Information-theoretic Bounds on the Generalization Error

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We consider a statistical model for finite-rank symmetric tensor factorization and prove a single-letter variational expression for its asymptotic mutual information when the tensor is of even order. The proof applies the adaptive interpolation method orig ...

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The aim of this work is to provide bounds connecting two probability measures of the same event using Rényi

\alpha

-Divergences and Sibson’s

\alpha

-Mutual Information, a generalization of respectively the Kullback-Leibler Divergence and Shannon’s Mutual ...

Strengthened Information-theoretic Bounds on the Generalization Error

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Mutual information for low-rank even-order symmetric tensor estimation

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