Learning to Prune in Training via Dynamic Channel Propagation

  title={Learning to Prune in Training via Dynamic Channel Propagation},
  author={Shibo Shen and Rongpeng Li and Zhifeng Zhao and Honggang Zhang and Yugeng Zhou},
  journal={2020 25th International Conference on Pattern Recognition (ICPR)},
  • Shibo Shen, Rongpeng Li, +2 authors Yugeng Zhou
  • Published 3 July 2020
  • Computer Science, Mathematics
  • 2020 25th International Conference on Pattern Recognition (ICPR)
In this paper, we propose a novel network training mechanism called “dynamic channel propagation” to prune the neural networks during the training period. In particular, we pick up a specific group of channels in each convolutional layer to participate in the forward propagation in training time according to the significance level of channel, which is defined as channel utility. The utility values with respect to all selected channels are updated simultaneously with the error back-propagation… 
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