Efficient Decentralized Deep Learning by Dynamic Model Averaging

Michael Kamp, Linara Adilova, Joachim Sicking +4

We propose an efficient protocol for decentralized training of deep neural networks from distributed data sources. The proposed protocol allows to handle different phases of model…