Robust Decentralized Personalized Federated Learning via Prediction-Constrained Neighborhood Collaboration
This paper proposes a robust decentralized personalized federated learning method R-DPFL, that enables clients to reduce the impact of Byzantine attacks via robust neighborhood direction estimation and history-based update trend prediction, rather than purely aggregating client models as in the existing work. In R-DPFL...
Xiao Ma, Hong Shen, Hui Tian et al.
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