Federated Multi-Source Domain Adaptation through Optimal Transport: A Privacy-Preserving Approach for Collaborative Learning

The core message of this paper is to propose a novel framework called Federated Multi-source Domain Adaptation through Optimal Transport (FMDA-OT) that combines optimal transport and federated learning to enable privacy-preserving multi-source domain adaptation without direct access to source domain data.