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This allows us to control the measure of an event under the joint, using the product of the marginals (typically easier to compute) and a measure of how much ...
This allows us to control the measure of an event under the joint, using the product of the marginals (typically easier to compute) and a measure of how much ...
Jan 14, 2020 · 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 ...
It can be derived from the optimization objective of maximizing the χ 2 -divergence, one of the f -mutual information measures (Csiszár, 1972; Esposito et al., ...
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Jan 14, 2020 · The aim of this work is to provide bounds connecting two probability measures of the same event using R\'enyi $\alpha$-Divergences and ...
Jun 26, 2023 · Amedeo Roberto Esposito , Michael Gastpar, Ibrahim Issa: Robust Generalization via f-Mutual Information. ISIT 2020: 2723-2728.
Abstract:The aim of this work is to provide bounds connecting two probability measures of the same event using Rényi $\alpha$-Divergences and Sibson's ...
Abstract—The aim of this work is to provide bounds connecting two probability measures of the same event using Rényi α-. Divergences and Sibson's α-Mutual ...
We propose a new approach to apply the chaining technique in conjunction with information-theoretic measures to bound the generalization error of machine ...
Abstract. We provide an information-theoretic framework for studying the generalization properties of ma- chine learning algorithms.