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Learning Transferable Features with Deep Adaptation Networks
時間 2020-12-23
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遷移學習
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經典文章DAN 總函數: 上面的公式中,J函數是一組有標籤樣本的損失,dk2是第l層的mk-mmd距離。 總函數調整的參數是θ,應該是1-8層(1-3層是固定的,4-5是fine-tune,6-8層是learn) ???fine-tune、learn的區別 kernel parameter β是怎麼學習的? 本文的創新點: (參考:對於DAN方法的解讀-Learni
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相關文章
1.
Learning Transferable Features with Deep Adaptation Networks
2.
翻譯「Learning Transferable Features with Deep Adaptation Networks」
3.
對於DAN方法的解讀-Learning Transferable Features with Deep Adaptation Networks
4.
How transferable are features in deep nerual networks? 【paper review】
5.
How transferable are features in deep neural networks?
6.
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7.
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8.
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