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Effective Approaches to Attention-based Neural Machine Translation論文筆記
時間 2020-12-24
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這篇文章在NMT(Neural machine translation)上嘗試了兩種簡單且有效的注意力機制:一個可以注意所有單詞的全局方法(global approach),和一個只看部分單詞的局部方法(local approach). 1.全局方法類似(Bahdanau et al.2015),但是結構更簡單, 2.局部方法可以看爲是hard和soft注意力機制(Xu et al.,2015)的
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相關文章
1.
【論文筆記】Effective Approaches to Attention-based Neural Machine Translation
2.
論文筆記(Attention 2)-----Effective Approaches to Attention-based Neural Machine Translation
3.
[EMNLP2015]Effective Approaches to Attention-based Neural Machine Translation
4.
Effective Approaches to Attention-based Neural Machine Translation 學習筆記
5.
Paper:Effective Approaches to Attention-based Neural Machine Translation
6.
【論文】on the properties of neural machine translation :Encoder-decoder approaches 閱讀筆記
7.
多標籤分類:Effective Approaches to Attention-based Neural Machine Translation
8.
Effective Approaches to Attention-based Neural Machine Translation之每日一篇
9.
論文筆記(attention 1)----NEURAL MACHINE TRANSLATION BY JOINTLY LEARNING TO ALIGN AND TRANSLATE
10.
Neural machine translation by jointly learning to align and translate論文閱讀筆記
>>更多相關文章<<