Weisheng Liao

FedRAC: Rolling Submodel Allocation for Collaborative Fairness in Federated Learning

Collaborative fairness in federated learning ensures that clients are rewarded according to their contributions, thereby fostering long-term participation among clients. However, existing methods often under-reward low-contributing clients in the early training stage and neglect critical issues (con