GC-Fed Accepted at Information Fusion

January 12, 2026

PublicationFederated LearningInformation Fusion

GC-Fed Accepted at Information Fusion

On January 12, 2026, our paper “GC-Fed: Gradient Centralized Federated Learning with Partial Client Participation” was accepted at Information Fusion (JCR IF 15.5, top-tier journal in AI).

Paper (DOI)
Code

GC-Fed workflow figure

Summary

GC-Fed proposes a gradient-centralized federated learning strategy designed for settings with partial client participation, with emphasis on improving convergence stability and practical scalability.