Under a Bayesian model of domain adaptation, the paper derives the optimal learner and shows that the posterior label entropy (PTLU) lower-bounds the target risk, providing a new hardness measure.
On the hardness of domain adaptation and the utility of unlabeled target samples
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On the Hardness of Unsupervised Domain Adaptation: Optimal Learners and Information-Theoretic Perspective
Under a Bayesian model of domain adaptation, the paper derives the optimal learner and shows that the posterior label entropy (PTLU) lower-bounds the target risk, providing a new hardness measure.