6 citations · 8 across the 7 of their papers we have counts for
7 papers
AS-FedBridge: Pseudo-Spike Bridge Distillation for Heterogeneous ANN-SNN Federated Learning
Shengyang Li, Yiting Dong, Liuyang Song +5
Federated learning enables collaborative model training across distributed edge devices while strictly preserving data privacy. To facilitate practical deployment on resource-const…
Communication Efficient Multiparty Private Set Intersection from Multi-Point Sequential OPRF
Xinyu Feng, Yukun Wang, Cong Li +5
Multiparty private set intersection (MPSI) allows multiple participants to compute the intersection of their locally owned data sets without revealing them. MPSI protocols can be c…
MH-pFLGB: Model Heterogeneous personalized Federated Learning via Global Bypass for Medical Image Analysis
Luyuan Xie, Manqing Lin, ChenMing Xu +7
In the evolving application of medical artificial intelligence, federated learning is notable for its ability to protect training data privacy. Federated learning facilitates colla…
pFLFE: Cross-silo Personalized Federated Learning via Feature Enhancement on Medical Image Segmentation
Luyuan Xie, Manqing Lin, Siyuan Liu +6
In medical image segmentation, personalized cross-silo federated learning (FL) is becoming popular for utilizing varied data across healthcare settings to overcome data scarcity an…
MH-pFLID: Model Heterogeneous personalized Federated Learning via Injection and Distillation for Medical Data Analysis
Luyuan Xie, Manqing Lin, Tianyu Luan +4
Federated learning is widely used in medical applications for training global models without needing local data access. However, varying computational capabilities and network arch…
SHISRCNet: Super-resolution And Classification Network For Low-resolution Breast Cancer Histopathology Image
Luyuan Xie, Cong Li, Zirui Wang +4
The rapid identification and accurate diagnosis of breast cancer, known as the killer of women, have become greatly significant for those patients. Numerous breast cancer histopath…
NCL: Textual Backdoor Defense Using Noise-augmented Contrastive Learning
Shengfang Zhai, Qingni Shen, Xiaoyi Chen +4
At present, backdoor attacks attract attention as they do great harm to deep learning models. The adversary poisons the training data making the model being injected with a backdoo…