dual learning for machine translation
对于翻译系统，如语言A翻译到语言B，通常需要大量的语言对来训练神经机器翻译，而数据量的增大会大大的增加成本。本文通过构建两个神经翻译网络，θAB和θBA，这两个网络分别用于将语言A翻译到语言B和语言B翻译到语言A。文章先采用少量的语言对训练好这两个模型。之后，采用无监督学习，训练这两个模型，具体为将语言A输入网络θAB，同时将θAB的输出输入到网络θBA中，再采用强化学习的思想，对网络θAB和网络
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相关文章
- 1. 论文阅读——Dual Learning for Machine Translation
- 2. 论文阅读：Dual Learning for Machine Translation
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