Channel Pruning for Accelerating Very Deep Neural Networks 论文笔记
转自：https://blog.csdn.net/zhongshaoyy/article/details/78551728 PDF Code 作者思路是基于CNN每一层都是稀疏地假设，考虑是否能找到neuron之间的关系，仅留下最具有代表性地neuron。 分为两步解决问题： 找出每一层具有代表性地neuron，我们利用lasso regression来进行类似model selection的过
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相关文章
- 1. Channel Pruning for Accelerating Very Deep Neural Networks
- 2. Channel Pruning for Accelerating Very Deep Neural Networks论文笔记
- 3. 论文笔记——Channel Pruning for Accelerating Very Deep Neural Networks
- 4. 【模型压缩】Channel Pruning for Accelerating Very Deep Neural Networks算法笔记
- 5. 代码开源：Channel Pruning for Accelerating Very Deep Neural Networks
- 6. 《Soft Filter Pruning for Accelerating Deep Convolutional Neural Networks》论文笔记
- 7. Global Sparse Momentum SGD for Pruning Very Deep Neural Networks 论文阅读笔记
- 8. 论文笔记——Data-free Parameter Pruning for Deep Neural Networks
- 9. 《FPGM：Filter Pruning via Geometric Median for Deep Convolutional Neural Networks Acceleration》论文笔记
- 10. 论文笔记：Filter Pruning via Geometric Median for Deep Convolutional Neural Networks Acceleration