Patent ID: 11887001
Assignee: INTEL CORPORATION
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 0:
1. An apparatus comprising:
a layer-wise pruning module to prune a specified set of parameters from each layer of a reference neural network model in accordance with a Joint Feed-forward and Backward Propagation Approximation (JFBPA) to generate a second neural network model having a higher sparsity rate than the reference neural network model, wherein a layer in the second neural network model is computed using the JFBPA based on a number of zero parameters in a corresponding matrix;
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, wherein the retraining of the layer in the second neural network model maintains the number of zero parameters; and
the retraining module to output the retrained second neural network model as a final neural network model if a specified target sparsity rate or a specified number of alternating pruning and retraining iterations has been reached, and to provide the retrained second neural network model to the layer-wise pruning module for additional pruning if both the specified target sparsity rate and the specified number of alternating pruning and retraining iterations have not been reached.