Open access
2026
Clustered Federated Learning With Contrastive Loss and Staleness-Aware Aggregation for LEO Satellite Constellations
Model Contrastive Federated Learning bridges the gap between distributed learning theory and practical satellite constraints, offering a scalable solution for real-time ML applications in dynamic space-terrestrial networks.
Ren Ozeki, Mohamed Rihan, Hamada Rizk et al.
· IEEE Open Journal of the Com... · 0 citations