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...
Finding related papers...
Discussions
(0)No comments yet
Be the first to share your thoughts!