FMDA-OT: Federated Multi-source Domain Adaptation Through Optimal Transport

arXiv:2404.06599v1 Announce Type: new
Abstract: Multi-source Domain Adaptation (MDA) aims to adapt models trained on multiple labeled source domains to an unlabeled target domain. In this paper, we introduce our approach as a collaborative MDA framework, which comprises two adaptation phases. Firstly, we conduct domain adaptation for each source individually with the target, utilizing optimal transport. Then, in the second phase, which constitutes the final part of the framework, we design the architecture of centralized federated learning to collaborate the …

abstract adapt arxiv collaborative cs.ai cs.lg domain domain adaptation domains framework multiple paper through transport type