DRACO: Decentralized Asynchronous Federated Learning over Row-Stochastic Wireless Networks
This paper introduces DRACO, a decentralized and asynchronous federated learning framework tailored for wireless networks where communication delays, node heterogeneity, and topology variations make traditional synchronous FL inefficient. Unlike centralized approaches, DRACO removes the need for a server and allows… Read More »DRACO: Decentralized Asynchronous Federated Learning over Row-Stochastic Wireless Networks

