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#machine learning Preprint Sep 2026

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. · 1 citation
#machine learning Preprint Sep 2026

Robust Decentralized Federated Distillation via Multi-Modality Knowledge Collaboration

This paper shows that the proposed method ensures a bounded Byzantine influence on both distillation gradients and individual client private gradients after cross-modality fusion, thereby enabling stable local optimization for honest clients under Byzantine distillation.

Xiao Ma, Hong Shen, Hui Tian et al. · 0 citations

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