SeqGAN: Sequence Generative Adversarial Nets with Policy Gradient
来源:互联网 发布:苹果瞄准镜软件 编辑:程序博客网 时间:2024/05/29 18:08
https://arxiv.org/abs/1609.05473
(Submitted on 18 Sep 2016 (v1), last revised 9 Dec 2016 (this version, v5))
As a new way of training generative models, Generative Adversarial Nets (GAN) that uses a discriminative model to guide the training of the generative model has enjoyed considerable success in generating real-valued data. However, it has limitations when the goal is for generating sequences of discrete tokens. A major reason lies in that the discrete outputs from the generative model make it difficult to pass the gradient update from the discriminative model to the generative model. Also, the discriminative model can only assess a complete sequence, while for a partially generated sequence, it is non-trivial to balance its current score and the future one once the entire sequence has been generated. In this paper, we propose a sequence generation framework, called SeqGAN, to solve the problems. Modeling the data generator as a stochastic policy in reinforcement learning (RL), SeqGAN bypasses the generator differentiation problem by directly performing gradient policy update. The RL reward signal comes from the GAN discriminator judged on a complete sequence, and is passed back to the intermediate state-action steps using Monte Carlo search. Extensive experiments on synthetic data and real-world tasks demonstrate significant improvements over strong baselines.
0 0
- SeqGAN: Sequence Generative Adversarial Nets with Policy Gradient
- SeqGAN: Sequence Generative Adversarial Nets with Policy Gradient
- [生成对抗网络] 论文研读-SeqGAN: Sequence Generative Adversarial Nets with Policy Gradient
- Improving Neural Machine Translation with Conditional Sequence Generative Adversarial Nets
- 论文引介 | NMT with Conditional Sequence Generative Adversarial Nets
- Generative Adversarial Nets
- Generative Adversarial Nets
- GAN: Generative Adversarial Nets
- Generative Adversarial Nets
- Generative Adversarial Nets
- Triple Generative Adversarial Nets
- Conditional Generative Adversarial Nets
- Generative Adversarial Nets
- 阅读小结:Generative Adversarial Nets
- Generative adversarial nets 论文笔记
- 汇总Generative Adversarial Nets资料
- Generative Adversarial Nets(译)
- Generative Adversarial Nets (GAN)解读
- 第一课:利用atom和xcode开发react-native的入门技巧(Mac)
- 修改表编码格式(解决中文乱码问题相关)
- 如何在Ubuntu 14.04上备份、恢复及迁移MongoDB数据库
- iOS版本最新分布概况
- iOS内存优化--大文件如何处理,内存映射
- SeqGAN: Sequence Generative Adversarial Nets with Policy Gradient
- eclipse 地址备忘
- Exynos4412裸机开发——中断处理
- 要提高SQL查询效率where语句条件的先后次序应如何写
- spring教程--JdbcTemplate详解
- CodeForces 605 C.Freelancer's Dreams(三分)
- [boolan]设计模式 观察者学习
- 将eclispe中项目导入到Android Studio中
- 【iOS学习】十五、Category