190 citations · 617 across the 19 of their papers we have counts for
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cs.LG2023★ 1 cited
Deep Reinforcement Learning Based Vehicle Selection for Asynchronous Federated Learning Enabled Vehicular Edge Computing
Qiong Wu, Siyuan Wang, Pingyi Fan +1
In the traditional vehicular network, computing tasks generated by the vehicles are usually uploaded to the cloud for processing. However, since task offloading toward the cloud wi…
cs.LG2022★ 1 cited
Asynchronous Federated Learning for Edge-assisted Vehicular Networks
Siyuan Wang, Qiong Wu, Qiang Fan +2
Vehicular networks enable vehicles support real-time vehicular applications through training data. Due to the limited computing capability, vehicles usually transmit data to a road…
cs.LG2021★ 1 cited
Differential Privacy Meets Federated Learning under Communication Constraints
Nima Mohammadi, Jianan Bai, Qiang Fan +3
The performance of federated learning systems is bottlenecked by communication costs and training variance. The communication overhead problem is usually addressed by three communi…