Glivenko-Cantelli for $f$-divergence

Fuente: arXiv
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Main Authors: Wang, Haoming, Lim, Lek-Heng
Format: Preprint
Published: 2025
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author Wang, Haoming
Lim, Lek-Heng
author_facet Wang, Haoming
Lim, Lek-Heng
contents We extend the celebrated Glivenko-Cantelli theorem, sometimes called the fundamental theorem of statistics, from its standard setting of total variation distance to all $f$-divergences. A key obstacle in this endeavor is to define $f$-divergence on a subcollection of a $σ$-algebra that forms a $π$-system but not a $σ$-subalgebra. This is a side contribution of our work. We will show that this notion of $f$-divergence on the $π$-system of rays preserves nearly all known properties of standard $f$-divergence, yields a novel integral representation of the Kolmogorov-Smirnov distance, and has a Glivenko-Cantelli theorem. We will also discuss the prospects of a Vapnik-Chervonenkis theory for $f$-divergence.
format Preprint
id arxiv_https___arxiv_org_abs_2503_17355
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Glivenko-Cantelli for $f$-divergence
Wang, Haoming
Lim, Lek-Heng
Statistics Theory
Machine Learning
60B10, 60F15, 60F25
We extend the celebrated Glivenko-Cantelli theorem, sometimes called the fundamental theorem of statistics, from its standard setting of total variation distance to all $f$-divergences. A key obstacle in this endeavor is to define $f$-divergence on a subcollection of a $σ$-algebra that forms a $π$-system but not a $σ$-subalgebra. This is a side contribution of our work. We will show that this notion of $f$-divergence on the $π$-system of rays preserves nearly all known properties of standard $f$-divergence, yields a novel integral representation of the Kolmogorov-Smirnov distance, and has a Glivenko-Cantelli theorem. We will also discuss the prospects of a Vapnik-Chervonenkis theory for $f$-divergence.
title Glivenko-Cantelli for $f$-divergence
topic Statistics Theory
Machine Learning
60B10, 60F15, 60F25
url https://arxiv.org/abs/2503.17355