6 citations · 18 across the 10 of their papers we have counts for
4 papers · 1 filter
Federated Domain Generalization for Image Recognition via Cross-Client Style Transfer
Junming Chen, Meirui Jiang, Qi Dou +1
Domain generalization (DG) has been a hot topic in image recognition, with a goal to train a general model that can perform well on unseen domains. Recently, federated learning (FL…
Tackling Long-Tailed Category Distribution Under Domain Shifts
Xiao Gu, Yao Guo, Zeju Li +5
Machine learning models fail to perform well on real-world applications when 1) the category distribution P(Y) of the training dataset suffers from long-tailed distribution and 2)…
Federated Learning from Only Unlabeled Data with Class-Conditional-Sharing Clients
Nan Lu, Zhao Wang, Xiaoxiao Li +3
Supervised federated learning (FL) enables multiple clients to share the trained model without sharing their labeled data. However, potential clients might even be reluctant to lab…
IOP-FL: Inside-Outside Personalization for Federated Medical Image Segmentation
Meirui Jiang, Hongzheng Yang, Chen Cheng +1
Federated learning (FL) allows multiple medical institutions to collaboratively learn a global model without centralizing client data. It is difficult, if possible at all, for such…