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DTSTART:20240331T030000
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DTSTAMP:20260424T143115Z
UID:1703171700@ist.ac.at
DTSTART:20231221T161500
DTEND:20231221T171500
DESCRIPTION:Speaker: Jonathan Husson\nhosted by Laszlo Erdös\nAbstract: In
  many applications of random matrix theory\, such as Principal Component A
 nalysis or the study of random landscapes\, the behaviour of the largest e
 igenvalue is of particular importance. In this talk\, we will consider a 
  model of generalized empirical covariance matrix and we will state a lar
 ge deviation principle for its largest eigenvalue. The main tool of the pr
 oof is the use of a spherical integral of rank one as a proxy for this lar
 gest eigenvalue. This makes it possible to tackle not only Gaussian entrie
 s but also so-called "sharp sub-Gaussian" entries such as Rademacher rando
 m variables. We then have a universality phenomenon - which is rather surp
 rising in the regime of large deviation - as well as an elegant representa
 tion for the rate function. This talk is based on a collaboration with Ben
  McKenna.
LOCATION:Heinzel Seminar Room (I21.EG.101)\, Office Building West\, ISTA\, 
 ISTA
ORGANIZER:birgit.oosthuizen-noczil@ist.ac.at 
SUMMARY:Jonathan Husson: Generalized empirical covariance matrices and larg
 e deviations
URL:https://talks-calendar.ista.ac.at/events/4675
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