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DTSTART:20070311T020000
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DTSTAMP:20210208T163119
DTSTART;TZID=America/Detroit:20210219T100000
DTEND;TZID=America/Detroit:20210219T110000
SUMMARY:Workshop / Seminar:Statistics Department Seminar Series: Jing Lei\, Associate Professor\, Department of Statistics and Data Science\, Carnegie Mellon University
DESCRIPTION:Abstract:  We consider the problem of testing the equality of the conditional distribution of a response variable given a set of covariates between two populations.  Such a testing problem is related to transfer learning and causal inference.  We develop a nonparametric procedure by combining recent advances in conformal prediction with some new ingredients such as a novel choice of conformity score and data-driven choices of weight and score functions. To our knowledge\, this is the first successful attempt of using conformal prediction for testing statistical hypotheses beyond exchangeability. Our method is suitable for modern machine learning scenarios where the data has high dimensionality and large sample sizes\, and can be effectively combined with existing classification algorithms to find good weight and score functions.  The performance of the proposed method is demonstrated in synthetic and real data examples.\n\nhttp://www.stat.cmu.edu/people/faculty/jingle/\n\nThis seminar will be livestreamed via Zoom https://umich.zoom.us/j/94350208889\nThere will be a virtual reception to follow
UID:80565-20740178@events.umich.edu
URL:https://events.umich.edu/event/80565
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:seminar
LOCATION:Off Campus Location
CONTACT:
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