3 citations · 3 across the 4 of their papers we have counts for
4 papers
On Federated Learning with Energy Harvesting Clients
Cong Shen, Jing Yang, Jie Xu
Catering to the proliferation of Internet of Things devices and distributed machine learning at the edge, we propose an energy harvesting federated learning (EHFL) framework in thi…
Context-Aware Online Client Selection for Hierarchical Federated Learning
Zhe Qu, Rui Duan, Lixing Chen +3
Federated Learning (FL) has been considered as an appealing framework to tackle data privacy issues of mobile devices compared to conventional Machine Learning (ML). Using Edge Ser…
How to Test the Randomness from the Wireless Channel for Security?
Zhe Qu, Shangqing Zhao, Jie Xu +2
We revisit the traditional framework of wireless secret key generation, where two parties leverage the wireless channel randomness to establish a secret key. The essence in the fra…
Resource Rationing for Wireless Federated Learning: Concept, Benefits, and Challenges
Cong Shen, Jie Xu, Sihui Zheng +1
We advocate a new resource allocation framework, which we term resource rationing, for wireless federated learning (FL). Unlike existing resource allocation methods for FL, resourc…