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TZID:America/Chicago
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DTSTART:20250309T030000
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DTSTART:20251102T010000
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BEGIN:VEVENT
DTSTAMP;TZID=America/Chicago:20260409T041538
UID:204400@calendar.wisc.edu
DTSTART;TZID=America/Chicago:20250314T120000
DTEND;TZID=America/Chicago:20250314T130000
DESCRIPTION:MM Optimization Algorithms for Analyzing Big Biomedical Data. D
 r. Zhao will present novel applications of the majorization-minimization (
 MM) principle in the big data setting. He will discuss derivation of a par
 allel block least squares algorithm that allows parallel update of regress
 ion coefficients with a large feature matrix partitioned by columns\; a de
 weighting technique for weighted least squares\; and an MM algorithm for f
 itting large-scale variance component model that provably converges faster
  than the classical EM algorithm. \n\nPasscode: 343271\n\nCONTACT: junjie.
 hu@wisc.edu\n\nURL: https://biostat.wisc.edu/seminars\n\nONLINE: https://u
 wmadison.zoom.us/j/99879638765
LOCATION:Auditorium\, Genetics-Biotechnology Center Building  (Also offered
  online)
SUMMARY:Biostatistics and Medical Informatics Department Seminar with Hua Z
 hao\, University of California Los Angeles
URL;VALUE=URI:https://biostat.wisc.edu/seminars
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