24 citations · 98 across the 12 of their papers we have counts for
17 papers
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…
Adversarial Machine Learning based Partial-model Attack in IoT
Zhengping Luo, Shangqing Zhao, Zhuo Lu +2
As Internet of Things (IoT) has emerged as the next logical stage of the Internet, it has become imperative to understand the vulnerabilities of the IoT systems when supporting div…
Client Selection and Bandwidth Allocation in Wireless Federated Learning Networks: A Long-Term Perspective
Jie Xu, Heqiang Wang
This paper studies federated learning (FL) in a classic wireless network, where learning clients share a common wireless link to a coordinating server to perform federated model tr…
The Tradeoff Between Privacy and Accuracy in Anomaly Detection Using Federated XGBoost
Mengwei Yang, Linqi Song, Jie Xu +2
Privacy has raised considerable concerns recently, especially with the advent of information explosion and numerous data mining techniques to explore the information inside large v…
When Attackers Meet AI: Learning-empowered Attacks in Cooperative Spectrum Sensing
Zhengping Luo, Shangqing Zhao, Zhuo Lu +2
Defense strategies have been well studied to combat Byzantine attacks that aim to disrupt cooperative spectrum sensing by sending falsified versions of spectrum sensing data to a f…