【Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huff】論文筆記
追隨Song Han大神的第二篇網絡壓縮論文（ICLR’16），論文鏈接：https://arxiv.org/abs/1510.00149 這篇論文是【Learning both Weights and Connections for Efficient Neural Networks】的升級版 效果： 大概能實現35-49倍的壓縮。 在ImageNet數據集上，將AlexNet所需的存儲量從24
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