[EMNLP2015]Effective Approaches to Attention-based Neural Machine Translation
neural machine translation有以下優點： (1) 有能力生成很長的詞序列 (2) 因爲不需要存儲巨大的短語詞表，所以需要很小的內存 (3) 解碼很容易 A： 介紹了兩種attention模型，其共同點是在每一步decoding時hidden state h t 都作爲輸入參與計算c t (1)global attention 在生成target word y t 時， in
相關文章
- 1. Paper：Effective Approaches to Attention-based Neural Machine Translation
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相關文章
- 1. Paper：Effective Approaches to Attention-based Neural Machine Translation
- 2. 【論文筆記】Effective Approaches to Attention-based Neural Machine Translation
- 3. 論文筆記(Attention 2)-----Effective Approaches to Attention-based Neural Machine Translation
- 4. Effective Approaches to Attention-based Neural Machine Translation 學習筆記
- 5. 多標籤分類：Effective Approaches to Attention-based Neural Machine Translation
- 6. Effective Approaches to Attention-based Neural Machine Translation之每日一篇
- 7. Effective Approaches to Attention-based Neural Machine Translation論文筆記
- 8. 【CS224n】Neural Machine Translation with Seq2Seq
- 9. Neural Machine Translation by Jointly Learning to Align and....
- 10. Neural Machine Translation by Jointly Learning to Align and Translate