Ensemble-Compression: A New Method for Parallel Training of Deep Neural Networks

2 Jun 2016Shizhao SunWei ChenJiang BianXiaoguang LiuTie-Yan Liu

Parallelization framework has become a necessity to speed up the training of deep neural networks (DNN) recently. Such framework typically employs the Model Average approach, denoted as MA-DNN, in which parallel workers conduct respective training based on their own local data while the parameters of local models are periodically communicated and averaged to obtain a global model which serves as the new start of local models... (read more)

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