On the Hardness of Unsupervised Domain Adaptation: Optimal Learners and Information-Theoretic Perspective

Zhiyi Dong, Zixuan Liu, Yongyi Mao

This paper studies the hardness of unsupervised domain adaptation (UDA) under covariate shift. We model the uncertainty that the learner faces by a distribution $\pi$ in the ground-t…