公开(公告)号：US20190197407A1

公开(公告)日：2019-06-27

申请号：US16328182

申请日：2016-09-26

Applicant: INTEL CORPORATION

Inventor： Anbang YAO ,  Yiwen GUO ,  Lin XU ,  Yan LIN ,  Yurong CHEN

IPC: G06N3/08 ,  G06N3/04 ,  G06F17/16

CPC classification number: G06N3/082 ,  G06F17/16 ,  G06N3/02 ,  G06N3/04 ,  G06N3/0445 ,  G06N3/0454 ,  G06N3/084

Abstract: An apparatus and method are described for reducing the parameter density of a deep neural network (DNN). A layer-wise pruning module to prune a specified set of parameters from each layer of a reference dense neural network model to generate a second neural network model having a relatively higher sparsity rate than the reference neural network model; a retraining module to retrain the second neural network model in accordance with a set of training data to generate a retrained second neural network model; and the retraining module to output the retrained second neural network model as a fmal neural network model if a target sparsity rate has been reached or to provide the retrained second neural network model to the layer-wise pruning model for additional pruning if the target sparsity rate has not been reached.