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Pruning-aware Sparse Regularization for Network Pruning

Published in arXiv (Cornell University) • Jan 18, 2022
NobleIDNI7P81W78R90S08
Authors:
Nanfei Jiang
,
Xu Zhao
,
Chaoyang Zhao

Abstract

Structural neural network pruning aims to remove the redundant channels in the deep convolutional neural networks (CNNs) by pruning the filters of less importance to the final output accuracy. To reduce the degradation of performance after pruning, many methods utilize the loss with sparse regulariz...

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