Analysis of Importance Decoupling Pruning Strategy Based on Batch Normalization Layer
This paper describes a deep learning automatic sparse pruning strategy that decouples through importance analysis,and forces channel level importance decoupling sparse training on neural networks through importance judgment.This method accurately decouples redundant channels and minimizes accuracy loss after pruning.
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