1 citations · 1 across the 5 of their papers we have counts for
Showing 2024Show all
3 papers · 1 filter
math.OC2024★ 1 cited
A Novel Privacy Enhancement Scheme with Dynamic Quantization for Federated Learning
Yifan Wang, Xianghui Cao, Shi Jin +1
Federated learning (FL) has been widely regarded as a promising paradigm for privacy preservation of raw data in machine learning. Although, the data privacy in FL is locally prote…
eess.SY2024
Augmented LRFS-based Filter: Holistic Tracking of Group Objects
Chaoqun Yang, Xiaowei Liang, Zhiguo Shi +2
This paper addresses the problem of group target tracking (GTT), wherein multiple closely spaced targets within a group pose a coordinated motion. To improve the tracking performan…
eess.SY2024
A Control-Recoverable Added-Noise-based Privacy Scheme for LQ Control in Networked Control Systems
Xuening Tang, Xianghui Cao, Wei Xing Zheng
As networked control systems continue to evolve, ensuring the privacy of sensitive data becomes an increasingly pressing concern, especially in situations where the controller is p…