Boost Decentralized Federated Learning in Vehicular Networks by Diversifying Data Sources

no code implementations • 5 Sep 2022 • Dongyuan Su, Yipeng Zhou, Laizhong Cui

To boost the convergence of DFL, a vehicle tunes the aggregation weight of each data source by minimizing the KL divergence of its state vector, and its effectiveness in diversifying data sources can be theoretically proved.

Federated Learning