2 papers
stat.ML2026
Unsupervised Domain Adaptation for Binary Classification with an Unobservable Source Subpopulation
Chao Ying, Jun Jin, Haotian Zhang +4
We study an unsupervised domain adaptation problem where the source domain consists of subpopulations defined by the binary label and a binary background (or environment) .…
stat.ME2025
Towards the Efficient Inference by Incorporating Automated Computational Phenotypes under Covariate Shift
Chao Ying, Jun Jin, Yi Guo +3
Collecting gold-standard phenotype data via manual extraction is typically labor-intensive and slow, whereas automated computational phenotypes (ACPs) offer a systematic and much f…