论文《Learning both Weights and Connections for Efficient Neural Network》阅读笔记
因为对深度压缩中的剪枝不太理解遂读了原文作者更早的这篇详细讲网络剪枝的文章点击打开链接 剪枝的过程为： 1.首先剪枝的前提是对已完成训练的网络 2.进行剪枝 要点：根据一个阈值去裁剪参数 a.阈值的确定：首先这个阈值相关于这一层权重的标准差（The pruning threshold is chosen as a quality parameter multiplied by the stan
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相关文章
- 1. 【Learning both Weights and Connections for Efficient Neural Networks】论文笔记
- 2. 《Learning both Weights and Connections for Efficient Neural Networks》论文笔记
- 3. 论文品读：Learning both Weights and Connections for Efficient Neural Networks
- 4. 【论文阅读】韩松《Efficient Methods And Hardware For Deep Learning》节选《Learning both Weights and Connections 》
- 5. 网络模型剪枝-论文阅读《Learning both Weights and Connections for Efficient Neural Networks》
- 6. 深度网络推理加速（Learning both Weights and Connections for Efficient Neural Networks）
- 7. 【论文阅读笔记】ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices
- 8. 论文阅读笔记：ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices
- 9. Machine Learning & Deep Learning 论文阅读笔记
- 10. 论文阅读笔记《Edge-Labeling Graph Neural Network for Few-shot Learning》