3 papers
cs.LG2025
FedDifRC: Unlocking the Potential of Text-to-Image Diffusion Models in Heterogeneous Federated Learning
Huan Wang, Haoran Li, Huaming Chen +3
Federated learning aims at training models collaboratively across participants while protecting privacy. However, one major challenge for this paradigm is the data heterogeneity is…
cs.CV2025
FedSC: Federated Learning with Semantic-Aware Collaboration
Huan Wang, Haoran Li, Huaming Chen +3
Federated learning (FL) aims to train models collaboratively across clients without sharing data for privacy-preserving. However, one major challenge is the data heterogeneity issu…
cs.LG2025
FedSKC: Federated Learning with Non-IID Data via Structural Knowledge Collaboration
Huan Wang, Haoran Li, Huaming Chen +5
With the advancement of edge computing, federated learning (FL) displays a bright promise as a privacy-preserving collaborative learning paradigm. However, one major challenge for…