AI RESEARCH
Domain-Skewed Federated Learning with Feature Decoupling and Calibration
arXiv CS.LG
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ArXi:2603.14238v1 Announce Type: new Federated learning (FL) allows distributed clients to collaboratively train a global model in a privacy-preserving manner. However, one major challenge is domain skew, where clients' data originating from diverse domains may hinder the aggregated global model from learning a consistent representation space, resulting in poor generalizable ability in multiple domains.