RL for Sentence Generation
本篇博文主要總結下臺大教授李宏毅深度學習課程中關於 seqGAN s e q G A N 的相關內容，並且添加了自己的一些思考。 Policy Gradient 衆所周知，強化學習的目標就是 Maximizing Expected Reward M a x i m i z i n g E x p e c t e d R e w a r d ，在 seqGAN s e q G A N 中，如
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相關文章
- 1. RL for Sentence Generation
- 2. 李宏毅：RL and GAN for sentence generation and chat-bot
- 3. Deep Reinforcement Learning for Dialogue Generation
- 4. Variational RL for POMDP
- 5. Attacks for RL
- 6. [EMNLP2015]A Neural Attention Model for Sentence Summarization
- 7. Review networks for caption generation
- 8. Convolutional Neural Network For Sentence Classification
- 9. Convolutional Neural Networks for Sentence Classification
- 10. 《Convolutional Neural Networks for Sentence Classification》