(11)[ICML15] Batch Norm: Accelerating Deep Network Training by Reducing Internal Covariate Shift
计划完成深度学习入门的126篇论文第十一篇，Google的Ioffe和Szegedy使用一种新的regularization方法或者说是新的initialization的方法Batch Normalization。 ABSTRACT&INTRODUCTION 摘要 由于训练过程中各层输入的分布随前一层参数的变化而变化，使得深度神经网络的训练变得复杂。这需要较低的学习率和谨慎的参数初始化，从而降低了
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- 1. (11)[ICML15] Batch Norm: Accelerating Deep Network Training by Reducing Internal Covariate Shift
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- 4. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift 论文翻译（转）
- 5. 《Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift》论文笔记
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相关文章
- 1. (11)[ICML15] Batch Norm: Accelerating Deep Network Training by Reducing Internal Covariate Shift
- 2. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift 论文解读
- 3. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
- 4. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift 论文翻译（转）
- 5. 《Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift》论文笔记
- 6. 【inv2】Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
- 7. 论文阅读 Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
- 8. 论文笔记：Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
- 9. [论文阅读] Batch Normalization: Accelerating Deep Network Training By Reducing Internal Covariate Shift
- 10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift论文翻译