152 citations · 327 across the 34 of their papers we have counts for
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cs.DC2022★ 14 cited
Dordis: Efficient Federated Learning with Dropout-Resilient Differential Privacy
Zhifeng Jiang, Wei Wang, Ruichuan Chen
Federated learning (FL) is increasingly deployed among multiple clients to train a shared model over decentralized data. To address privacy concerns, FL systems need to safeguard t…
cs.DC2022★ 7 cited
Pisces: Efficient Federated Learning via Guided Asynchronous Training
Zhifeng Jiang, Wei Wang, Baochun Li +1
Federated learning (FL) is typically performed in a synchronous parallel manner, where the involvement of a slow client delays a training iteration. Current FL systems employ a par…
cs.DC2021★ 34 cited
Towards Efficient Synchronous Federated Training: A Survey on System Optimization Strategies
Zhifeng Jiang, Wei Wang, Bo Li +1
The increasing demand for privacy-preserving collaborative learning has given rise to a new computing paradigm called federated learning (FL), in which clients collaboratively trai…