77 citations · 165 across the 17 of their papers we have counts for
4 papers · 1 filter
Automated Customization of On-Thing Inference for Quality-of-Experience Enhancement
Yang Bai, Lixing Chen, Shaolei Ren +1
The rapid uptake of intelligent applications is pushing deep learning (DL) capabilities to Internet-of-Things (IoT). Despite the emergence of new tools for embedding deep neural ne…
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…
Autodidactic Neurosurgeon: Collaborative Deep Inference for Mobile Edge Intelligence via Online Learning
Letian Zhang, Lixing Chen, Jie Xu
Recent breakthroughs in deep learning (DL) have led to the emergence of many intelligent mobile applications and services, but in the meanwhile also pose unprecedented computing ch…
Bandwidth Allocation for Multiple Federated Learning Services in Wireless Edge Networks
Jie Xu, Heqiang Wang, Lixing Chen
This paper studies a federated learning (FL) system, where \textit{multiple} FL services co-exist in a wireless network and share common wireless resources. It fills the void of wi…