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UID:20260415T071951EDT-7259n3OJMA@132.216.98.100
DTSTAMP:20260415T111951Z
DESCRIPTION: \n\nTitle: Learning mixtures of Gaussians\n\n \n\nAbstract:\n
 \nDistribution learning lies at the intersection of statistics\, theoretic
 al computer science and machine learning. We give an overview of this area
 \, with the problem of learning mixtures of high-dimensional Gaussians as 
 a running example. In particular\, we prove nearly tight sample complexity
  bounds for this problem in the density estimation model.\n\nBased on join
 t work with Hassan Ashtiani\, Shai Ben-David\, Luc Devroye\, Nick Harvey\,
  Christopher Liaw\, Yani Plan\, and Tommy Reddad.\n
DTSTART:20190122T213000Z
DTEND:20190122T223000Z
LOCATION:Room 1104\, Burnside Hall\, CA\, QC\, Montreal\, H3A 0B9\, 805 rue
  Sherbrooke Ouest
SUMMARY:Abbas Mehrabian - McGill University
URL:https://www.mcgill.ca/mathstat/channels/event/abbas-mehrabian-mcgill-un
 iversity-293420
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