2025
FedCFA: Alleviating Simpson’s Paradox in Model Aggregation with Counterfactual Federated Learning
AAAI 2025technical
Federated learning (FL) is a promising technology for data privacy and distributed optimization, but it suffers from data imbalance and heterogeneity among clients. Existing FL methods try to solve the problems by aligning client with server model or by correcting client model with control variables…