Globally Soft Filter Pruning For Efficient Convolutional Neural Networks

ICLR 2019 Ke XuXiaoyun WangQun JiaJianjing AnDong Wang

This paper propose a cumulative saliency based Globally Soft Filter Pruning (GSFP) scheme to prune redundant filters of Convolutional Neural Networks (CNNs).Specifically, the GSFP adopts a robust pruning method, which measures the global redundancy of the filter in the whole model by using the soft pruning strategy. In addition, in the model recovery process after pruning, we use the cumulative saliency strategy to improve the accuracy of pruning... (read more)

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