Original paper
Filter Pruning via Geometric Median for Deep Convolutional Neural Networks Acceleration
Published: Jun 1, 2019
Abstract
Previous works utilized “smaller-norm-less-important” criterion to prune filters with smaller norm values in a convolutional neural network. In this paper, we analyze this norm-based criterion and point out that its effectiveness depends on two requirements that are not always met: (1) the norm deviation of the filters should be large; (2) the minimum norm of the filters should be small. To solve this problem, we propose a novel filter pruning...
Paper Details
Title
Filter Pruning via Geometric Median for Deep Convolutional Neural Networks Acceleration
Published Date
Jun 1, 2019
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