Communication efficient distributed learning of neural networks in Big Data environments using Spark

Distributed (or federated) training of neural networks is an important approach to reduce the training time significantly. Previous experiments on communication efficient distributed learning have shown that model averaging, even if provably correct only in case of convex loss functions, is also working for the training of neural networks in some cases, however restricted to simple examples with r...