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Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
時間 2021-01-02
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正則化
算法
神經網絡
計算機視覺
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系統網絡
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Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift 1 Introduction 深度學習極大地提高了視覺、語言和許多其他領域的藝術水平。隨機梯度下降(SGD)被證明是訓練深層網絡的一種有效方法,SGD變量如動量(Sutskever et al.,2013)和Ada
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相關文章
1.
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift 論文解讀
2.
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift 論文翻譯(轉)
3.
《Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift》論文筆記
4.
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
5.
【inv2】Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
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論文筆記:Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
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