Nokia Corporation

Microsoft Mobile Oy

Intel Corporation

Yan Lin

Wei Wang

Anbang Yao

Lin Xu

Yurong Chen

Yiwen Guo

Saemee Yoon

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 final 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.

Method and apparatus for reducing the parameter density of a deep neural network (DNN)

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Growing community of inventors

Beijing, China

Yan Lin