34 citations · 64 across the 4 of their papers we have counts for
4 papers
CHASe: Client Heterogeneity-Aware Data Selection for Effective Federated Active Learning
Jun Zhang, Jue Wang, Huan Li +3
Active learning (AL) reduces human annotation costs for machine learning systems by strategically selecting the most informative unlabeled data for annotation, but performing it in…
Data-Importance Aware User Scheduling for Communication-Efficient Edge Machine Learning
Dongzhu Liu, Guangxu Zhu, Jun Zhang +1
With the prevalence of intelligent mobile applications, edge learning is emerging as a promising technology for powering fast intelligence acquisition for edge devices from distrib…
An Overview of Attacks and Defences on Intelligent Connected Vehicles
Mahdi Dibaei, Xi Zheng, Kun Jiang +9
Cyber security is one of the most significant challenges in connected vehicular systems and connected vehicles are prone to different cybersecurity attacks that endanger passengers…
Client-Edge-Cloud Hierarchical Federated Learning
Lumin Liu, Jun Zhang, S. H. Song +1
Federated Learning is a collaborative machine learning framework to train a deep learning model without accessing clients' private data. Previous works assume one central parameter…