BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Talks.cam//talks.cam.ac.uk//
X-WR-CALNAME:Talks.cam
BEGIN:VEVENT
SUMMARY:A gradient flow approach to quantization of measures - Mikaela Iac
 obelli (DPMMS)
DTSTART:20151019T140000Z
DTEND:20151019T150000Z
UID:TALK61869@talks.cam.ac.uk
CONTACT:Harsha Hutridurga
DESCRIPTION:The problem of quantization of a $d$-dimension probability\ndi
 stribution  by discrete probabilities with a given number of points\ncan\n
 be stated as follows: Given a probability density  $\\rho$\, approximate\n
 it\nin the Wasserstein metric  by a convex combination of a finite number\
 n$N$\nof Dirac masses.\nIn a recent paper we studied a gradient flow appro
 ach to this problem in\none dimension.\nBy embedding the problem in $L^2$\
 , we find a continuous version of it\nthat\ncorresponds to the limit as th
 e number of particles tends to infinity.\nUnder some suitable regularity a
 ssumptions on the density\, we prove\nuniform\nstability and quantitative 
 convergence result for the discrete and\ncontinuous dynamics.
LOCATION:CMS\, MR13
END:VEVENT
END:VCALENDAR