190 citations · 292 across the 27 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.LG2023★ 2 cited
FedLP: Layer-wise Pruning Mechanism for Communication-Computation Efficient Federated Learning
Zheqi Zhu, Yuchen Shi, Jiajun Luo +4
Federated learning (FL) has prevailed as an efficient and privacy-preserved scheme for distributed learning. In this work, we mainly focus on the optimization of computation and co…
cs.LG2021
How global observation works in Federated Learning: Integrating vertical training into Horizontal Federated Learning
Shuo Wan, Jiaxun Lu, Pingyi Fan +3
Federated learning (FL) has recently emerged as a transformative paradigm that jointly train a model with distributed data sets in IoT while avoiding the need for central data coll…