Google Research

Robust Domain Adaptation

Annals of Mathematics and Artificial Intelligence, vol. 71 Issue 4 (2014), 365–380

Abstract

We derive a generalization bound for domain adaptation by using the properties of robust algorithms. Our new bound depends on λ-shift, a measure of prior knowledge regarding the similarity of source and target domain distributions. Based on the generalization bound, we design SVM variants for binary classification and regression domain adaptation algorithms.

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