二值網絡訓練--A Empirical Study of Binary Neural Networks' Optimisation
A Empirical Study of Binary Neural Networks’ Optimisation ICLR2019 https://github.com/mi-lad/studying-binary-neural-networks 本文得到的幾個結論如下： ADAM for optimising the objective, (2) not using early stoppin
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相關文章
- 1. 二值網絡訓練--Training Competitive Binary Neural Networks from Scratch
- 2. 二值網絡--Structured Binary Neural Networks for Accurate Image Classification and Semantic Segmentation
- 3. 二值網絡--XNOR-Net: ImageNet Classification Using Binary Convolutional Neural Networks
- 4. 二值神經網絡（Binary Neural Networks）最新綜述
- 5. 二值神經網絡（Binary Neural Network，BNN）
- 6. Applications of Graph Neural Networks
- 7. Local Binary Convolutional Neural Networks
- 8. An Empirical Study of Real-world Polymorphic Code Injection Attacks
- 9. 論文筆記：Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling
- 10. 論文閱讀：An Empirical Study of Spatial Attention Mechanisms in Deep Networks