359 citations · 776 across the 7 of their papers we have counts for
Showing 2020Show all
3 papers · 1 filter
cs.LG2020★ 8 cited
Stochastic Client Selection for Federated Learning with Volatile Clients
Tiansheng Huang, Weiwei Lin, Li Shen +2
Federated Learning (FL), arising as a privacy-preserving machine learning paradigm, has received notable attention from the public. In each round of synchronous FL training, only a…
cs.LG2020★ 235 cited
An Efficiency-boosting Client Selection Scheme for Federated Learning with Fairness Guarantee
Tiansheng Huang, Weiwei Lin, Wentai Wu +3
The issue of potential privacy leakage during centralized AI's model training has drawn intensive concern from the public. A Parallel and Distributed Computing (or PDC) scheme, ter…
cs.DC2020★ 101 cited
Accelerating Federated Learning over Reliability-Agnostic Clients in Mobile Edge Computing Systems
Wentai Wu, Ligang He, Weiwei Lin +1
Mobile Edge Computing (MEC), which incorporates the Cloud, edge nodes and end devices, has shown great potential in bringing data processing closer to the data sources. Meanwhile,…