• PaperReview
  • Introduction
  • Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding
  • Binarized Neural Networks
  • Trained Ternary Quantization
  • DSD
  • INCREMENTAL NETWORK QUANTIZATION
  • Distilling the Knowledge in a Neural Network
  • Learning bothWeights and Connections for Efficient Neural Networks
  • BinaryConnect
  • Googlenet
  • SqueezeNet
  • vgg
  • Deep Residual Learning
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Introduction

Readings:

浅析张量分解 www.voidcn.com/article/p-xkaagvud-bbs.html

https://www.oreilly.com.cn/ideas/?p=801

http://blog.csdn.net/electech6/article/details/72822009

http://www.wikihow.com/Compress-Data-Using-Huffman-Encoding

http://www.wildml.com/deep-learning-glossary/

https://gab41.lab41.org/lab41-reading-group-deep-compression-9c36064fb209

https://jacobgil.github.io/deeplearning/pruning-deep-learning

http://www.deeplearningbook.org/

Datasets

Wall Street Journal

https://catalog.ldc.upenn.edu/docs/LDC94S13A/wsj1.txt

LibriSpeech ASR corpus

http://www.openslr.org/resources.php

https://github.com/NervanaSystems/deepspeech

Github

https://dragonfive.github.io/2017-08-05/cnn_improve/ 神经网络的压缩优化方法总结

http://blog.csdn.net/wspba/article/details/76039135 深度学习模型压缩方法综述

http://blog.csdn.net/wspba/article/details/75675554

http://blog.csdn.net/wspba/article/details/75671573

https://github.com/yiwenguo/Dynamic-Network-Surgery/blob/master/Makefile Dynamic-Network-Surgery

https://www.nvidia.com/en-us/data-center/gpu-accelerated-applications/tensorflow/

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