Batch Normalization: Accelerating Deep Network Training b y Reducing Internal Covariate Shift
挖個墳，最近纔看了batch normalize的原始paper，是Christian Szegedy（googlenet作者）的工作，已經在實際工作裏用的很多了，再看這個paper還是能感受到作者很深厚的理論基礎以及實現能力。 Motivation： 深度學習剛出來的時候我們就會遇到這樣的問題，如果學習率比較大那麼訓練會不收斂或者直接nan飛掉，而且初始化參數的分佈也十分重要，設置的不好就會導致
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相關文章
- 1. [論文閱讀] 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論文翻譯
- 4. 論文筆記：Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
- 5. 《Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift》論文筆記
- 6. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift 論文解讀
- 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 論文翻譯（轉）
- 9. 論文閱讀 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