代碼開源：Channel Pruning for Accelerating Very Deep Neural Networks
代碼開源：Channel Pruning for Accelerating Very Deep Neural Networks [PDF] [Code] 這是我們今年 ICCV 2017 的工作。 基於CNN每一層都是稀疏地假設，我們考慮是否能找到neuron之間的關係，僅留下最具有代表性地neuron？ 分爲兩步解決問題： 找出每一層具有代表性地neuron，我們利用lasso regressi
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相關文章
- 1. Channel Pruning for Accelerating Very Deep Neural Networks
- 2. Channel Pruning for Accelerating Very Deep Neural Networks論文筆記
- 3. 【模型壓縮】Channel Pruning for Accelerating Very Deep Neural Networks算法筆記
- 4. 論文筆記——Channel Pruning for Accelerating Very Deep Neural Networks
- 5. Channel Pruning for Accelerating Very Deep Neural Networks 論文筆記
- 6. 《Soft Filter Pruning for Accelerating Deep Convolutional Neural Networks》論文筆記
- 7. Global Sparse Momentum SGD for Pruning Very Deep Neural Networks 論文閱讀筆記
- 8. 【Comprssion】《Deep Compression：Compressing Deep Neural Networks with Pruning，Trained QuantizationXXX》
- 9. Very Deep Convolutional Networks for Text Classification
- 10. 《Image Super-Resolution Using Very Deep Residual Channel Attention Networks》