96 citations · 211 across the 28 of their papers we have counts for
4 papers · 1 filter
Personalizing or Not: Dynamically Personalized Federated Learning with Incentives
Zichen Ma, Yu Lu, Wenye Li +1
Personalized federated learning (FL) facilitates collaborations between multiple clients to learn personalized models without sharing private data. The mechanism mitigates the stat…
Performance Optimization for Variable Bitwidth Federated Learning in Wireless Networks
Sihua Wang, Mingzhe Chen, Christopher G. Brinton +3
This paper considers improving wireless communication and computation efficiency in federated learning (FL) via model quantization. In the proposed bitwidth FL scheme, edge devices…
Service Delay Minimization for Federated Learning over Mobile Devices
Rui Chen, Dian Shi, Xiaoqi Qin +3
Federated learning (FL) over mobile devices has fostered numerous intriguing applications/services, many of which are delay-sensitive. In this paper, we propose a service delay eff…
Towards Heterogeneous Clients with Elastic Federated Learning
Zichen Ma, Yu Lu, Zihan Lu +3
Federated learning involves training machine learning models over devices or data silos, such as edge processors or data warehouses, while keeping the data local. Training in heter…