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(10) [JMLR14] Dropout: A Simple Way to Prevent Neural Networks from Overfitting
時間 2020-12-24
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計劃完成深度學習入門的126篇論文第十篇,多倫多大學的Geoffrey Hinton·和Alex Krizhevsky使用一種新的regularization方法Dropout。 ABSTRACT&INTRODUCTION 摘要 具有大量參數的深度神經網絡是非常強大的機器學習系統。然而,在這樣的網絡中,過擬合是一個嚴重的問題。大型網絡的使用也很緩慢,通過在測試時結合許多不同的大型神經網絡的預測,很
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相關文章
1.
(10) [JMLR14] Dropout: A Simple Way to Prevent Neural Networks from Overfitting
2.
Dropout:A Simple Way to Prevent Neural Networks from Overfitting
3.
【論文精讀】Dropout: A Simple Way to Prevent Neural Networks from Overfitting
4.
譯:《Dropout: A Simple Way to Prevent Neural Networks from Overfitting》
5.
Dropout: A Simple Way to Prevent Neural Networks from Over tting 論文閱讀
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論文筆記2——Dropout:A simple way to prevent neural networks from overfitting
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