Differentially Private Byzantine-Robust Federated Learning

Federated learning is a collaborative machine learning framework where a global model is trained by different organizations under the privacy restrictions. Promising as it is, privacy and robustness issues emerge when an adversary attempts to infer the private information from the exchanged paramete...

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Veröffentlicht in:	IEEE transactions on parallel and distributed systems 2022-12, Vol.33 (12), p.3690-3701
Hauptverfasser:	Ma, Xu, Sun, Xiaoqian, Wu, Yuduo, Liu, Zheli, Chen, Xiaofeng, Dong, Changyu
Format:	Artikel
Sprache:	eng
Schlagworte:	byzantine-robust Collaborative work Computational modeling Data models Differential privacy Federated learning Machine learning Privacy Servers Training
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