1 citations · 3 across the 4 of their papers we have counts for
4 papers
FedDBP: Enhancing Federated Prototype Learning with Dual-Branch Features and Personalized Global Fusion
Ningzhi Gao, Siquan Huang, Leyu Shi +1
Federated prototype learning (FPL), as a solution to heterogeneous federated learning (HFL), effectively alleviates the challenges of data and model heterogeneity.However, existing…
White-Box Multi-Objective Adversarial Attack on Dialogue Generation
Yufei Li, Zexin Li, Yingfan Gao +1
Pre-trained transformers are popular in state-of-the-art dialogue generation (DG) systems. Such language models are, however, vulnerable to various adversarial samples as studied i…
Multi-metrics adaptively identifies backdoors in Federated learning
Siquan Huang, Yijiang Li, Chong Chen +2
The decentralized and privacy-preserving nature of federated learning (FL) makes it vulnerable to backdoor attacks aiming to manipulate the behavior of the resulting model on speci…
Try to Avoid Attacks: A Federated Data Sanitization Defense for Healthcare IoMT Systems
Chong Chen, Ying Gao, Leyu Shi +1
Healthcare IoMT systems are becoming intelligent, miniaturized, and more integrated into daily life. As for the distributed devices in the IoMT, federated learning has become a top…