2 papers
cs.LG2025
CoSIFL: Collaborative Secure and Incentivized Federated Learning with Differential Privacy
Zhanhong Xie, Meifan Zhang, Lihua Yin
Federated learning (FL) has emerged as a promising paradigm for collaborative model training while preserving data locality. However, it still faces challenges from malicious or co…
cs.LG2024
Private and Communication-Efficient Federated Learning based on Differentially Private Sketches
Meifan Zhang, Zhanhong Xie, Lihua Yin
Federated learning (FL) faces two primary challenges: the risk of privacy leakage due to parameter sharing and communication inefficiencies. To address these challenges, we propose…