【論文閱讀】韓鬆《Efficient Methods And Hardware For Deep Learning》節選《Deep compression》
Trained Quantization and Deep Compression 本章內容來在ICLR 2016論文《Deep compression: Compressing deep neural networks with pruning, trained quantization and huffman coding》。 DeepCompression由剪枝、量化和變長編碼組成，它可將神經
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相關文章
- 1. 【論文閱讀】韓鬆《Efficient Methods And Hardware For Deep Learning》節選《Learning both Weights and Connections 》
- 2. 【韓鬆博士畢業論文】Efficient methods and hardware for deep learning
- 3. 韓鬆博士畢業論文Efficient methods and hardware for deep learning論文詳解
- 4. CS231n Lecture 15 | Efficient Methods and Hardware for Deep Learning
- 5. 論文閱讀：《Wide & Deep Learning for Recommender Systems》
- 6. 論文閱讀-《Learning Deep Features for Discriminative Localization》
- 7. 論文閱讀15：Massively Parallel Methods for Deep Reinforcement Learning
- 8. 【論文閱讀】Deep Residual Learning for Image Recognition
- 9. 論文閱讀——Deep Residual Learning for Image Recognition
- 10. Machine Learning & Deep Learning 論文閱讀筆記