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/Paris
BEGIN:DAYLIGHT
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
DTSTART:20170326T010000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
DTSTART:20171029T010000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=Europe/Paris:20171106T140000
DTEND;TZID=Europe/Paris:20171106T151500
DTSTAMP:20260715T083838
CREATED:20171017T085633Z
LAST-MODIFIED:20171017T085633Z
UID:11948-1509976800-1509981300@crest.science
SUMMARY:Martin KROLL (ENSAE-ParisTech CREST) - "On minimax optimal and adaptive estimation of linear functionals in inverse Gaussian sequence space models"
DESCRIPTION:\nThe Statistical Seminar: Every Monday at 2:00 pm.\nTime: 2:00 pm – 3:15 pm\nDate: 6th of November 2017\nPlace: Room 3001.\nMartin KROLL (ENSAE-ParisTech CREST) “On minimax optimal and adaptive estimation of linear functionals in inverse Gaussian sequence space models“ \nAbstract \nWe consider an inverse problem in a Gaussian sequence space model where the multiplication operator is not known but only available via noisy observations. Our aim is not to reconstruct the solution itself but the value of a linear functional of the solution. In our setup the optimal rate depends on two different noise levels\, the noise level concerning the observation of the transformed solution and the noise level concerning the noisy observation of the operator.  We consider this problem from a minimax point of view and obtain upper and lower bounds under smoothness assumptions on the multiplication operator and the unknown solution.  Finally\, we sketch an approach to the adaptive estimation in the given model using a method combining both model selection and the Goldenshluger-Lepski method. \nThis is joint work in progress with Cristina Butucea (ENSAE) and Jan Johannes (Heidelberg). \nOrganizers:\nCristina BUTUCEA\, Alexandre TSYBAKOV\, Eric MOULINES\, Mathieu ROSENBAUM\nSponsors:\nCREST-CMAP\n \n\n
URL:https://crest.science/event/martin-kroll-ensae-paristech-crest-on-minimax-optimal-and-adaptive-estimation-of-linear-functionals-in-inverse-gaussian-sequence-space-models/
CATEGORIES:Statistics
ATTACH;FMTTYPE=:
END:VEVENT
END:VCALENDAR