Active learning via transductive experimental design

Abstract

This paper considers the problem of selecting the most informative experiments x to get measurements y for learning a regression model y = f(x). We propose a novel and simple concept for active learning, transductive experimental design, that explores available unmeasured experiments (i.e., unlabeled data) and has a better scalability in comparison with… (More)
DOI: 10.1145/1143844.1143980

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