27 citations · 51 across the 11 of their papers we have counts for
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cs.LG2023
Age-Based Scheduling for Mobile Edge Computing: A Deep Reinforcement Learning Approach
Xingqiu He, Chaoqun You, Tony Q. S. Quek
With the rapid development of Mobile Edge Computing (MEC), various real-time applications have been deployed to benefit people's daily lives. The performance of these applications…
cs.LG2023★ 12 cited
Automated Federated Learning in Mobile Edge Networks -- Fast Adaptation and Convergence
Chaoqun You, Kun Guo, Gang Feng +2
Federated Learning (FL) can be used in mobile edge networks to train machine learning models in a distributed manner. Recently, FL has been interpreted within a Model-Agnostic Meta…
cs.LG2022★ 27 cited
Semi-Synchronous Personalized Federated Learning over Mobile Edge Networks
Chaoqun You, Daquan Feng, Kun Guo +2
Personalized Federated Learning (PFL) is a new Federated Learning (FL) approach to address the heterogeneity issue of the datasets generated by distributed user equipments (UEs). H…