模型剪枝学习路线

1.论文 - Learning both Weights and Connections for Efficient Neural Networks

https://xmfbit.github.io/2018/03/14/paper-network-prune-hansong/

2.论文 - Learning Structured Sparsity in Deep Neural Networks

https://xmfbit.github.io/2018/02/24/paper-ssl-dnn/

 

3.论文记录-Pruning Filters For Efficient ConvNets

https://blog.youkuaiyun.com/u013082989/article/details/77943240

4.exploring the efficacy of pruning for model compression论文笔记

https://blog.youkuaiyun.com/liujianlin01/article/details/80816000

 

5.模型压缩：Networks Slimming-Learning Efficient Convolutional Networks through Network Slimming

https://blog.youkuaiyun.com/u011995719/article/details/78788336

https://blog.youkuaiyun.com/u014380165/article/details/79969132

 

6.论文笔记：ThiNet——一种filter级的模型裁剪算法

https://blog.youkuaiyun.com/u014380165/article/details/77763037

https://blog.youkuaiyun.com/wspba/article/details/77427960

https://www.cnblogs.com/zhonghuasong/p/7648967.html

7.RETHINKING THE VALUE OF NETWORK PRUNING

https://www.jiqizhixin.com/articles/2018-10-22-6

https://blog.youkuaiyun.com/zhangjunhit/article/details/83506306