Convergence-Efficient Satellite-Ground Federated Learning for LEO Mega Constellations Optical Networks

We propose an efficient converged satellite-ground federated learning framework by quickly converging parameters to reduce the training time. Simulation results show that it can improve the global aggregation speed.