MetaPruning: Meta Learning for Automatic Neural Network Channel Pruning

ICCV 2019 Zechun LiuHaoyuan MuXiangyu ZhangZichao GuoXin YangTim Kwang-Ting ChengJian Sun

In this paper, we propose a novel meta learning approach for automatic channel pruning of very deep neural networks. We first train a PruningNet, a kind of meta network, which is able to generate weight parameters for any pruned structure given the target network... (read more)

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