On the Value of Target Data in Transfer Learning

Authors: Steve Hanneke, Samory Kpotufe

Abstract

We aim to understand the value of additional labeled or unlabeled target data in transfer learning, for any given amount of source data; this is motivated by practical questions around minimizing sampling costs, whereby, target data is usually harder or costlier to acquire than source data, but can yield better accuracy.

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