Equivalence of Informations Characterizes Bregman Divergences

Fuente: arXiv
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Autore principale: Chodrow, Philip S.
Natura: Preprint
Pubblicazione: 2025
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author Chodrow, Philip S.
author_facet Chodrow, Philip S.
contents Bregman divergences are a class of distance-like comparison functions which play fundamental roles in optimization, statistics, and information theory. One important property of Bregman divergences is that they cause two useful formulations of information content (in the sense of variability or non-uniformity) in a weighted collection of vectors to agree. In this note, we show that this agreement in fact characterizes the class of Bregman divergences; they are the only divergences which generate this agreement for arbitrary collections of weighted vectors.
format Preprint
id arxiv_https___arxiv_org_abs_2501_02104
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Equivalence of Informations Characterizes Bregman Divergences
Chodrow, Philip S.
Information Theory
68P30
H.1.1
Bregman divergences are a class of distance-like comparison functions which play fundamental roles in optimization, statistics, and information theory. One important property of Bregman divergences is that they cause two useful formulations of information content (in the sense of variability or non-uniformity) in a weighted collection of vectors to agree. In this note, we show that this agreement in fact characterizes the class of Bregman divergences; they are the only divergences which generate this agreement for arbitrary collections of weighted vectors.
title Equivalence of Informations Characterizes Bregman Divergences
topic Information Theory
68P30
H.1.1
url https://arxiv.org/abs/2501.02104