Author

Wei Ke

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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

#machine learning Preprint Sep 2026

Fine-grained Distributed Backdoor Attacks in Federated Learning

Federated learning, as a privacy-preserving distributed machine learning paradigm, faces significant threats from backdoor attacks. Compared to centralized attacks, distributed backdoor attacks are more harmful but require more poisoned samples to compensate for the loss of trigger strength due to decomposition. Fixed...

Jian Wang, Hong Shen, Wei Ke et al. · 0 citations