Mathematics > Numerical Analysis
[Submitted on 21 Sep 2022 (v1), last revised 10 Mar 2023 (this version, v3)]
Title:Quantitative Stability of Barycenters in the Wasserstein Space
View PDFAbstract:Wasserstein barycenters define averages of probability measures in a geometrically meaningful way. Their use is increasingly popular in applied fields, such as image, geometry or language processing. In these fields however, the probability measures of interest are often not accessible in their entirety and the practitioner may have to deal with statistical or computational approximations instead. In this article, we quantify the effect of such approximations on the corresponding barycenters. We show that Wasserstein barycenters depend in a H{ö}lder-continuous way on their marginals under relatively mild assumptions. Our proof relies on recent estimates that quantify the strong convexity of the dual quadratic optimal transport problem and a new result that allows to control the modulus of continuity of the push-forward operation under a (not necessarily smooth) optimal transport map.
Submission history
From: Alex Delalande [view email] [via CCSD proxy][v1] Wed, 21 Sep 2022 09:26:11 UTC (452 KB)
[v2] Wed, 8 Mar 2023 09:58:09 UTC (479 KB)
[v3] Fri, 10 Mar 2023 10:26:48 UTC (187 KB)
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