Neural Symbolic Machines: Learning Semantic Parsers on Freebase with Weak Supervision读书笔记
利用Lisp语言的形式表示问题的semantic，可以通过程序执行得到检索答案 整个系统由三部分组成：computer，programmer，manager computer是可以执行程序的部分 manager是提供weak supervision的部分 主要的解析部分为programmer programmer基于带attention的seq2seq模型，为了使得程序能够解析出符号和变量
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相关文章
- 1. Merging Weak and Active Supervision for Semantic Parsing论文笔记
- 2. 【Neural-Symbolic】方向的研究工作核心思想一览
- 3. Learning-Pixel-level-Semantic-Affinity-with-Image-level-Supervision
- 4. 论文：Learning Matching Models with Weak Supervision for Response Selection in Retrieval-based Chatbots
- 5. cousera“Neural NetWorks and Deep learning"读书笔记
- 6. Multi-Cue Zero-Shot Learning with Strong Supervision阅读笔记CVPR2016收录
- 7. Machine Learning & Deep Learning 论文阅读笔记
- 8. More Accurate Question Answering on Freebase阅读笔记
- 9. 【论文笔记】Semantic Parsing on Freebase from Question-Answer Pairs
- 10. 《Hands-On Machine Learning with Scikit-Learn&TensorFlow》读书笔记