Abstract: 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 ...

Abstract: Aiming at the data security problems existing in the traditional data aggregation scheme in the power Internet of Things, this paper proposes a fault-tolerant privacy-protecting data ...

Abstract: As an ambitious training paradigm, federated learning has garnered increasing attention in recent years, which enables collaborative training of a global model without accessing users’ ...