Sequence to Sequence Learning with Neural Networks学习笔记
论文的主要创新点 提出了序列到序列的学习方法 提出的背景 DNN的限制： 输入和输出向量维度固定，实际上很多序列问题中的序列长度不是已知先验 单个RNN 的限制： 输入和输出等长，且要一一对齐且对齐已知，无法应用到输入输出不等长且对应关系为非montonic 解决方案 两个RNN理论可行 一个负责将输入充列map 为固定大小的vector（背景向量，含有整个输入句子的信息），另一个RNN将背景向列
相关文章
- 1. Sutskever2014_Sequence to Sequence Learning with Neural Networks
- 2. Paper：Sequence to Sequence Learning with Neural Networks
- 3. (25)[NIPS14] Sequence to Sequence Learning with Neural Networks
- 4. 《Sequence to Sequence Learning with Neural Networks》阅读笔记
- 5. GRAPH2SEQ: GRAPH TO SEQUENCE LEARNING WITH ATTENTION-BASED NEURAL NETWORKS
- 6. 【论文阅读】Sequence to Sequence Learning with Neural Networks
- 7. Sequence to Sequence Learning with Neural Networks 论文内容介绍
- 8. Sequence to Sequence Learning with Neural Networks论文翻译
- 9. Sequence to Sequence Learning with Neural Networks，从RNN开始
- 10. 论文阅读：Sequence to Sequence Learning with Neural Networks
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相关文章
- 1. Sutskever2014_Sequence to Sequence Learning with Neural Networks
- 2. Paper：Sequence to Sequence Learning with Neural Networks
- 3. (25)[NIPS14] Sequence to Sequence Learning with Neural Networks
- 4. 《Sequence to Sequence Learning with Neural Networks》阅读笔记
- 5. GRAPH2SEQ: GRAPH TO SEQUENCE LEARNING WITH ATTENTION-BASED NEURAL NETWORKS
- 6. 【论文阅读】Sequence to Sequence Learning with Neural Networks
- 7. Sequence to Sequence Learning with Neural Networks 论文内容介绍
- 8. Sequence to Sequence Learning with Neural Networks论文翻译
- 9. Sequence to Sequence Learning with Neural Networks，从RNN开始
- 10. 论文阅读：Sequence to Sequence Learning with Neural Networks