Derives target-domain prediction models and proposes distribution matching to estimate subpopulation proportions in unsupervised domain adaptation with an unobservable source subpopulation, with asymptotic guarantees and an upper bound on prediction error.
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Unsupervised Domain Adaptation for Binary Classification with an Unobservable Source Subpopulation
Derives target-domain prediction models and proposes distribution matching to estimate subpopulation proportions in unsupervised domain adaptation with an unobservable source subpopulation, with asymptotic guarantees and an upper bound on prediction error.