##Statistics Seminar##\\ Department of Mathematical Sciences ^ **DATE:**|Thursday, October 21, 2021 | ^ **TIME:**|1:15pm -- 2:15pm | ^ **LOCATION:**|Zoom meeting | ^ **SPEAKER:**|Baozhen Wang, Binghamton University | ^ **TITLE:**|Covariate Shift by Kernel Mean Matching | \\ **Abstract** Given sets of observations of training and test data, the authors consider the problem of re-weighting the training data such that its distribution more closely matches that of the test data. They achieve this goal by matching covariate distributions between training and test sets in a high dimensional feature space (specifically, a reproducing kernel Hilbert space). This approach does not require distribution estimation. Instead, the sample weights are obtained by a simple quadratic programming procedure.