FedDRL: Trustworthy Federated Learning Model Fusion Method Based on Staged Reinforcement Learning
Leiming Chen,
Weishan Zhang,
Cihao Dong
et al.
Abstract:Federated learning facilitates collaborative data analysis among multiple participants while preserving user privacy. However, conventional federated learning approaches, typically employing weighted average techniques for model fusion, confront two significant challenges: 1. The inclusion of malicious models in the fusion process can drastically undermine the accuracy of the aggregated global model. 2. Due to the heterogeneity problem of devices and data, the number of client samples does not determine the we… Show more
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