5 papers
Adaptive Stepsizes With Certified Convergence in Distributed Gradient Tracking With Quadratic Costs
Yifan Wang, Luca Ballotta, Ruggero Carli +3
In this work, we propose an adaptive stepsize rule with guaranteed convergence for Distributed Gradient Tracking applied to scalar quadratic problems with heterogeneous curvatures.…
Pursuing Optimal Stepsize in Adaptive Gradient-Based Quadratic Optimization
Yifan Wang, Luca Ballotta, Ruggero Carli +2
In this paper, we address the problem of achieving fast convergence in gradient descent for quadratic functions without relying on a priori knowledge of global function parameters.…
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…
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…
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…