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Statistics Seminar
Department of Mathematical Sciences

DATE:Thursday, April 28, 2022
TIME:1:15pm – 2:15pm
LOCATION:Zoom meeting
SPEAKER:Baozhen Wang, Binghamton University
TITLE:A theory of learning from different domains


Discriminative learning methods for classification perform well when training and test data are drawn from the same distribution. Often, however, we have plentiful labeled training data from a source domain but wish to learn a classifier which performs well on a target domain with a different distribution and little or no labeled training data. The authors investigate two questions. First, under what conditions can a classifier trained from source data be expected to perform well on target data? Second, given a small amount of labeled target data, how should we combine it during training with the large amount of labeled source data to achieve the lowest target error at test time?

seminars/stat/220428.txt · Last modified: 2022/04/25 08:17 by qyu