Understanding Multi-Source Domain Adaptation for Feature Selection

In multi-source domain adaptation, the importance of learning approximately shared features is highlighted to improve population risk on both source and target tasks. The proposed statistical framework distinguishes content from environmental features based on their correlation to labels across domains.