Exploring Instance Relation for Decentralized Multi-Source Domain Adaptation

Multi-source domain adaptation aims to transfer knowledge from multiple labeled source domains to an unlabeled target domain and reduce the domain shift. Considering data privacy and storage cost, the data from different domains are isolated, which leads to the difficulty of domain adaptation. To reduce the domain shift on the decentralized source domains and target domain, we propose an instance relation consistency method for decentralized multi-source domain adaptation. Specifically, we utilize the models from other domains as bridges to conduct domain adaptation. We impose inter-domain instance relation consistency on the isolated source and target domain to transfer the semantic relation knowledge across different domain models. Meanwhile, we exploit intra-domain instance relation consistency to learn the intrinsic semantic relation across different data views. Experiments on three benchmarks indicate the effectiveness of our method for decentralized multi-source domain adaptation.