dual learning for machine translation
對於翻譯系統，如語言A翻譯到語言B，通常需要大量的語言對來訓練神經機器翻譯，而數據量的增大會大大的增加成本。本文通過構建兩個神經翻譯網絡，θAB和θBA，這兩個網絡分別用於將語言A翻譯到語言B和語言B翻譯到語言A。文章先採用少量的語言對訓練好這兩個模型。之後，採用無監督學習，訓練這兩個模型，具體爲將語言A輸入網絡θAB，同時將θAB的輸出輸入到網絡θBA中，再採用強化學習的思想，對網絡θAB和網絡
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相關文章
- 1. 論文閱讀——Dual Learning for Machine Translation
- 2. 論文閱讀：Dual Learning for Machine Translation
- 3. Machine Learning Techniques -2-Dual Support Vector Machine
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- 7. Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation
- 8. Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation之每日一篇
- 9. 翻譯：Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation
- 10. Netural Machine Translation By Joinly Learning To Align And Translate