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:20230509T103000
DTEND;TZID=Europe/Helsinki:20230509T113000
DTSTAMP:20260711T062450
CREATED:20230411T075908Z
LAST-MODIFIED:20230504T053421Z
UID:14862-1683628200-1683631800@crest.science
SUMMARY:Steffen GRÜNEWALDER - " Compressed Empirical Measures"
DESCRIPTION:Statistical Seminar: \nTime: 10:30 pm – 11:30 pm\nDate: 9th of May 2023\nPlace: Room 3001 + ZOOM \nSteffen GRÜNEWALDER – Compressed Empirical Measures \n  \nAbstract: \nI will discuss some of my recent results on compressing the empirical measure in the context of finite dimensional reproducing kernel Hilbert spaces (RKHSs). \nThe aim is to significantly reduce the size of the sample while preserving minimax optimal rates of convergence. Such a reduction in size is of crucial importance when working with kernel methods in the context of large-scale data since kernel methods scale poorly with the sample size. In the RKHS context\, an embedding of the empirical measure is contained in a convex set within an RKHS and can be approximated by using convex optimization techniques. Such an approximation gives rise to a small core-set of data points. A key quantity that controls the size of such a core-set is the size of the largest ball that fits within the convex set and which is centred at the embedding of the empirical measure. I will give an overview of how high probability lower bounds on the size of such a ball can be derived before discussing how the approach can be adapted to standard problems such as non-linear regression.  (The talk will be based on an extended version of https://arxiv.org/pdf/2204.08847.pdf). \n  \nLink : https://zoom.us/j/92070463949?pwd=bFNyNVh6SW5QWWZkSnd1ajlxcEpQZz09  \n  \nOrganizers:\nCristina BUTUCEA (CREST)\, Alexandre TSYBAKOV (CREST)\, Karim LOUNICI (CMAP) \, Jaouad MOURTADA (CREST)\nSponsors:\nCREST-CMAP \n
URL:https://crest.science/event/steffen-grunewalder-to-be-announced/
CATEGORIES:Statistics
ATTACH;FMTTYPE=:
END:VEVENT
END:VCALENDAR