most citedAuditing Privacy Defenses in Federated Learning via Generative Gradient Leakage

8 citations · 13 across the 2 of their papers we have counts for

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2 papers

cs.CV2022★ 8 cited

Auditing Privacy Defenses in Federated Learning via Generative Gradient Leakage

Zhuohang Li, Jiaxin Zhang, Luyang Liu +1

Federated Learning (FL) framework brings privacy benefits to distributed learning systems by allowing multiple clients to participate in a learning task under the coordination of a…

cs.LG2021★ 5 cited

Byzantine-robust Federated Learning through Spatial-temporal Analysis of Local Model Updates

Zhuohang Li, Luyang Liu, Jiaxin Zhang +1

Federated Learning (FL) enables multiple distributed clients (e.g., mobile devices) to collaboratively train a centralized model while keeping the training data locally on the clie…