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stat.ML2026
When few labeled target data suffice: a theory of semi-supervised domain adaptation via fine-tuning from multiple adaptive starts
Wooseok Ha, Yuansi Chen
Semi-supervised domain adaptation (SSDA) seeks to achieve accurate predictions in a target domain with limited labeled target data by exploiting abundant source and unlabeled targe…
stat.ML2025
Prominent Roles of Conditionally Invariant Components in Domain Adaptation: Theory and Algorithms
Keru Wu, Yuansi Chen, Wooseok Ha +1
Domain adaptation (DA) is a statistical learning problem that arises when the distribution of the source data used to train a model differs from that of the target data used to eva…