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cs.LG2019
DC-S3GD: Delay-Compensated Stale-Synchronous SGD for Large-Scale Decentralized Neural Network Training
Alessandro Rigazzi
Data parallelism has become the de facto standard for training Deep Neural Network on multiple processing units. In this work we propose DC-S3GD, a decentralized (without Parameter…
cs.NE2019★ 4 cited
Recombination of Artificial Neural Networks
Aaron Vose, Jacob Balma, Alex Heye +5
We propose a genetic algorithm (GA) for hyperparameter optimization of artificial neural networks which includes chromosomal crossover as well as a decoupling of parameters (i.e.,…