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PRODID:-//University of Utah Math Department//Data analysis with low-dimensional structures//EN
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X-WR-CALNAME:Data analysis with low-dimensional structures
X-WR-CALDESC:Data analysis with low-dimensional structures at University of Utah Mathematics Department
X-WR-TIMEZONE:America/Denver
BEGIN:VEVENT
UID:20170117T160000-wenjing-liao@math.utah.edu
DTSTART;TZID=America/Denver:20170117T160000
DTEND;TZID=America/Denver:20170117T170000
DTSTAMP:20260922T150858Z
SUMMARY:Data analysis with low-dimensional structures
DESCRIPTION:Speaker: Wenjing Liao\, Johns Hopkins University\n\nHigh-dimensional data arise in many fields of contemporary science and introduce new challenges in statistical learning. We model data sets as samples from a probability measure in R^D. When D is large, the well-known curse of dimensionality implies that an enormous amount of training data are …

LOCATION:JWB 335

URL:https://www.math.utah.edu/research/colloquia/2017-01-17-wenjing-liao/
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