BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//CREST - ECPv5.1.3//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:CREST
X-ORIGINAL-URL:https://crest.science
X-WR-CALDESC:Events for CREST
BEGIN:VTIMEZONE
TZID:Europe/Helsinki
BEGIN:DAYLIGHT
TZOFFSETFROM:+0200
TZOFFSETTO:+0300
TZNAME:EEST
DTSTART:20230326T010000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0300
TZOFFSETTO:+0200
TZNAME:EET
DTSTART:20231029T010000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=Europe/Helsinki:20230123T140000
DTEND;TZID=Europe/Helsinki:20230123T151500
DTSTAMP:20260711T105019
CREATED:20230113T083742Z
LAST-MODIFIED:20230113T083742Z
UID:14546-1674482400-1674486900@crest.science
SUMMARY:Lénaïc CHIZAT (EPFL) -  “Grid-free\, Debiaised\, Stable Entropic Wasserstein Barycenters”
DESCRIPTION:Statistical Seminar: Every Monday at 2:00 pm.\nTime: 2:00 pm – 3:15 pm\nDate: 23th of January 2023\nPlace: Room 3001 \nLénaïc CHIZAT (EPFL) “Grid-free\, Debiaised\, Stable Entropic Wasserstein Barycenters” \nAbstract: \nThe notion of “Wasserstein barycenter” is a natural way to define the average a family of probability measures but suffer from a high computational and statistical complexity\, particularly in high dimension. In this talk\, we introduce a formulation of entropy-regularized Wasserstein barycenters that enjoys favorable optimization\, approximation\, and statistical properties. This barycenter is defined as the unique probability measure that minimizes the sum of entropic optimal transport costs with respect to a family of given probability measures\, plus an entropy term. We show that: (i) this notion of barycenter lends itself naturally to a grid-free optimization algorithm which\, in the mean-field limit\, converges globally at an exponential rate\, (ii) it is debiased\, in the sense that it is a better approximation of the unregularized Wasserstein barycenter than the naive entropic Wasserstein barycenter and that (iii) it can be estimated at the parametric rate: given n samples from each of the probability measures\, the barycenter converges to the population barycenter at a rate n^{-1/2}\, as measured in relative entropy. \n  \n  \nOrganizers:\nCristina BUTUCEA (CREST)\, Alexandre TSYBAKOV (CREST)\, Karim LOUNICI (CMAP) \, Jaouad MOURTADA (CREST)\nSponsors:\nCREST-CMAP \n
URL:https://crest.science/event/lenaic-chizat-epfl-grid-free-debiaised-stable-entropic-wasserstein-barycenters/
CATEGORIES:Statistics
ATTACH;FMTTYPE=:
END:VEVENT
END:VCALENDAR