韓鬆博士畢業論文Efficient methods and hardware for deep learning論文詳解
論文由三部分構成，也是韓鬆在博士期間的工做，相關論文與解析見下面：node Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman coding： http://www.javashuo.com/article/p-orxjpdki-nb.html DS
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相關文章
- 1. 【韓鬆博士畢業論文】Efficient methods and hardware for deep learning
- 2. 【論文閱讀】韓鬆《Efficient Methods And Hardware For Deep Learning》節選《Learning both Weights and Connections 》
- 3. 【論文閱讀】韓鬆《Efficient Methods And Hardware For Deep Learning》節選《Deep compression》
- 4. CS231n Lecture 15 | Efficient Methods and Hardware for Deep Learning
- 5. 韓鬆 EIE： Efficient Inference Engine on Compressed Deep Neural Network論文詳解
- 6. 韓鬆Deep compression論文講解——PPT加說明文字
- 7. [論文解讀]Test Selection for Deep Learning Systems
- 8. 論文筆記之：Asynchronous Methods for Deep Reinforcement Learning
- 9. 【Learning both Weights and Connections for Efficient Neural Networks】論文筆記
- 10. 論文理解 Deep Residual Learning for Image Recognition