TowardsReliableModelSelectionforUnsupervised DomainAdaptation: AnEmpiricalStudyandA CertifiedBaseline

Existing approaches can be categorized into two types. The first type involves leveraging labeled source data for target-domain model selection [9,14-16]. The second type designs unsupervised metrics based on priors of the learned target-domain structure and utilizes the metrics for model selection[17,19,18,20].