35 citations · 36 across the 3 of their papers we have counts for
3 papers
cs.LG2022★ 35 cited
Confederated Learning: Federated Learning with Decentralized Edge Servers
Bin Wang, Jun Fang, Hongbin Li +2
Federated learning (FL) is an emerging machine learning paradigm that allows to accomplish model training without aggregating data at a central server. Most studies on FL consider…
cs.IT2022★ 1 cited
Over-the-Air Federated Multi-Task Learning via Model Sparsification and Turbo Compressed Sensing
Haoming Ma, Xiaojun Yuan, Zhi Ding +2
To achieve communication-efficient federated multitask learning (FMTL), we propose an over-the-air FMTL (OAFMTL) framework, where multiple learning tasks deployed on edge devices s…
cs.LG2021
Over-the-Air Federated Multi-Task Learning
Haoming Ma, Xiaojun Yuan, Dian Fan +3
In this letter, we introduce over-the-air computation into the communication design of federated multi-task learning (FMTL), and propose an over-the-air federated multi-task learni…