Learning to Transfer Examples for Partial Domain Adaptation

Understand

Domain adaptation is critical for learning in new and unseen environments.

• With domain adversarial training, deep networks can learn disentangled and transferable features that effectively diminish the dataset shift between the source and target domains for knowledge transfer.
• In the era of Big Data, the ready availability of large-scale labeled datasets has stimulated wide interest in partial domain adaptation (PDA), which transfers a recognizer from a labeled large domain to an unlabeled small domain.
• It extends standard domain adaptation to the scenario where target labels are only a subset of source labels.