The emerging paradigm of Federated Learning enables mobile users to collaboratively train a model without disclosing their privacy-sensitive data. Nevertheless, data collected from different may not be independent and identically distributed. Thus directly applying the trained new user usually leads performance degradation due so-called domain shift. Unsupervised Domain Adaptation is an effecti...