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PRODID:-//University of Utah Math Department//Robust and Scalable Inference for Big Data//EN
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X-WR-CALNAME:Robust and Scalable Inference for Big Data
X-WR-CALDESC:Robust and Scalable Inference for Big Data at University of Utah Mathematics Department
X-WR-TIMEZONE:America/Denver
BEGIN:VEVENT
UID:20160209T160000-lizhen-lin@math.utah.edu
DTSTART;TZID=America/Denver:20160209T160000
DTEND;TZID=America/Denver:20160209T170000
DTSTAMP:20260922T150858Z
SUMMARY:Robust and Scalable Inference for Big Data
DESCRIPTION:Speaker: Lizhen Lin\, University of Texas at Austin\n\nWhile theoretically justified and computationally efficient point estimators were developed in robust estimation for many problems, robust Bayesian analogues are not sufficiently well-understood. We propose a novel approach to Bayesian analysis that is provably robust to the presence of outliers and …

LOCATION:LCB 219

URL:https://www.math.utah.edu/research/colloquia/2016-02-09-lizhen-lin/
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