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DESCRIPTION:Title: Weighted empirical processes \n\n\n	Abstract:\n\n\nEmpiri
 cal processes concern the uniform behavior of averaged sums over a sample 
 of observations where the sums are indexed by a class of functions. Classi
 cal empirical processes typically study the empirical distribution functio
 n over the real line\, while more modern empirical processes study much mo
 re general indexing function classes (e.g.\, Vapnik-Chervonenkis class\, s
 moothness class)\; typical results include moment bounds and deviation ine
 qualities. In this talk we will survey some of these results\, but for the
  weighted empirical process that is obtained by weighing the original proc
 ess by a factor related to the standard deviation of the process\, which w
 ill make the resulting process more difficult to bound. Applications to mu
 ltivaraite rank order statistics and residual empirical processes will be 
 discussed.\n\n\n	Speaker\n\n\nDr. Yue Zhao is an Assistant Professor in the
  Department of Mathematics at University of York\, UK. He studied experime
 ntal cosmology (Ph.D. from Princeton in 2010) before switching to statisti
 cs (Ph.D. from Cornell in 2015). After postdoctoral studies at McGill (201
 5-16) and KU Leuven (2016-19)\, He joined York in 2019. His research mainl
 y focuses on copula and high-dimensional statistics\, and tools from empir
 ical process theory and U-statistics/U-processes.\n\nhttps://www.york.ac.u
 k/maths/staff/yue-zhao/#profile-content\n\nZoom Link\n\n			Meeting ID: 843 08
 65 5572\n\n			Passcode: 690084\n		 \n
DTSTART:20210910T193000Z
DTEND:20210910T203000Z
SUMMARY:Dr. Yue Zhao (University of York)
URL:https://www.mcgill.ca/channels/channels/event/dr-yue-zhao-university-yo
 rk-333220
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