4 papers
Federated Learning with Domain Shift Eraser
Zheng Wang, Zihui Wang, Xiaoliang Fan +1
Federated learning (FL) is emerging as a promising technique for collaborative learning without local data leaving their devices. However, clients' data originating from diverse do…
Federated Graph Learning for Cross-Domain Recommendation
Ziqi Yang, Zhaopeng Peng, Zihui Wang +6
Cross-domain recommendation (CDR) offers a promising solution to the data sparsity problem by enabling knowledge transfer across source and target domains. However, many recent CDR…
Selective Knowledge Sharing for Personalized Federated Learning Under Capacity Heterogeneity
Zheng Wang, Zhaopeng Peng, Zihui Wang +1
Federated Learning (FL) stands to gain significant advantages from collaboratively training capacity-heterogeneous models, enabling the utilization of private data and computing po…
FedSAC: Dynamic Submodel Allocation for Collaborative Fairness in Federated Learning
Zihui Wang, Zheng Wang, Lingjuan Lyu +6
Collaborative fairness stands as an essential element in federated learning to encourage client participation by equitably distributing rewards based on individual contributions. E…