3 papers
math.OC2026
Enhancing Accuracy in Differentially Private Distributed Optimization Through Sensitivity Reduction
Furan Xie, Bing Liu, Li Chai
In this paper, we investigate the problem of differentially private distributed optimization. Recognizing that lower sensitivity leads to higher accuracy, we analyze the key factor…
cs.LG2025
A Weighted Gradient Tracking Privacy-Preserving Method for Distributed Optimization
Furan Xie, Bing Liu, Li Chai
This paper investigates the privacy-preserving distributed optimization problem, aiming to protect agents' private information from potential attackers during the optimization proc…
math.OC2024
Cryptography-Based Privacy-Preserving Method for Distributed Optimization over Time-Varying Directed Graphs with Enhanced Efficiency
Bing Liu, Furan Xie, Li Chai
In this paper, we study the privacy-preserving distributed optimization problem, aiming to prevent attackers from stealing the private information of agents. For this purpose, we p…