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First provide a summary of the paper, and then address the following criteria: Quality, clarity, originality and significance. Paper ID: 39 Title: Robust Classification Under Sample Selection Bias NOTE: Due to the short reviewing time and out of fairness to the other papers I was reviewing, I DID NOT do more than glance over the supplementary material. In most cases, I therefore did not verify that results claimed by the authors are correct, but instead checked that they are plausible. Summary: This paper is about how to adjust a classifier when the training set is not representative of the test set; a canonical example is active learning, but the problem can also appear in recalibration. The goal is to find an effective method in the finite-sample regime, since most results are asymptotics.