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【Learning both Weights and Connections for Efficient Neural Networks】論文筆記
時間 2020-12-23
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追隨Song Han大神的第一篇網絡壓縮論文(NIPS’15),論文鏈接:https://arxiv.org/abs/1506.02626 這篇論文只是簡單介紹了裁剪的思路,並沒有涉及到網絡加速。 效果: 作者用了4個網絡實驗 Lenet-300-100, pruning reduces the number of weights by 12× Lenet-5, pruning reduces t
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相關文章
1.
《Learning both Weights and Connections for Efficient Neural Networks》論文筆記
2.
論文品讀:Learning both Weights and Connections for Efficient Neural Networks
3.
論文《Learning both Weights and Connections for Efficient Neural Network》閱讀筆記
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網絡模型剪枝-論文閱讀《Learning both Weights and Connections for Efficient Neural Networks》
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【論文閱讀】韓鬆《Efficient Methods And Hardware For Deep Learning》節選《Learning both Weights and Connections 》
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