FedImp: Enhancing Federated Learning Convergence with Impurity-Based Weighting

Hai Anh Tran, Cuong Ta, Truong X. Tran

Federated Learning (FL) is a collaborative paradigm that enables multiple devices to train a global model while preserving local data privacy. A major challenge in FL is the non-In…