Batch Normalization: Accelerating Deep Network Training b y Reducing Internal Covariate Shift
挖个坟，最近才看了batch normalize的原始paper，是Christian Szegedy（googlenet作者）的工作，已经在实际工作里用的很多了，再看这个paper还是能感受到作者很深厚的理论基础以及实现能力。 Motivation： 深度学习刚出来的时候我们就会遇到这样的问题，如果学习率比较大那么训练会不收敛或者直接nan飞掉，而且初始化参数的分布也十分重要，设置的不好就会导致
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相关文章
- 1. [论文阅读] Batch Normalization: Accelerating Deep Network Training By Reducing Internal Covariate Shift
- 2. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
- 3. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift论文翻译
- 4. 论文笔记：Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
- 5. 《Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift》论文笔记
- 6. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift 论文解读
- 7. 【inv2】Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
- 8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift 论文翻译（转）
- 9. 论文阅读 Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
- 10. (11)[ICML15] Batch Norm: Accelerating Deep Network Training by Reducing Internal Covariate Shift