6 citations · 18 across the 10 of their papers we have counts for
5 papers · 1 filter
FedSoup: Improving Generalization and Personalization in Federated Learning via Selective Model Interpolation
Minghui Chen, Meirui Jiang, Qi Dou +2
Cross-silo federated learning (FL) enables the development of machine learning models on datasets distributed across data centers such as hospitals and clinical research laboratori…
Client-Level Differential Privacy via Adaptive Intermediary in Federated Medical Imaging
Meirui Jiang, Yuan Zhong, Anjie Le +2
Despite recent progress in enhancing the privacy of federated learning (FL) via differential privacy (DP), the trade-off of DP between privacy protection and performance is still u…
Fair Federated Medical Image Segmentation via Client Contribution Estimation
Meirui Jiang, Holger R Roth, Wenqi Li +6
How to ensure fairness is an important topic in federated learning (FL). Recent studies have investigated how to reward clients based on their contribution (collaboration fairness)…
FedDBL: Communication and Data Efficient Federated Deep-Broad Learning for Histopathological Tissue Classification
Tianpeng Deng, Yanqi Huang, Guoqiang Han +7
Histopathological tissue classification is a fundamental task in computational pathology. Deep learning-based models have achieved superior performance but centralized training wit…
On Fairness of Medical Image Classification with Multiple Sensitive Attributes via Learning Orthogonal Representations
Wenlong Deng, Yuan Zhong, Qi Dou +1
Mitigating the discrimination of machine learning models has gained increasing attention in medical image analysis. However, rare works focus on fair treatments for patients with m…