A Federated Deep Learning Framework for Privacy Preservation and Communication Efficiency

no code implementations • 22 Jan 2020 • Tien-Dung Cao, Tram Truong-Huu, Hien Tran, Khanh Tran

However, its deployment in practice has been hurdled by two issues: the privacy of data that has to be aggregated centrally for model training and high communication overhead due to transmission of a large amount of data usually geographically distributed.

Federated Learning Privacy Preserving