<A Critical Review of Recurrent Neural Networks for Sequence Learning>阅读笔记
最近要学习RNN相关知识，根据知乎的建议，首先阅读了这篇经典论文。边读边想遍记录。 一、3个问题 1. 为什么一定要是序列模型？ 像SVM、LR、前向反馈网络是建立在 “独立”假设的基础上，更多模型则是人为地去构造前后顺序。但即使这样，上述模型仍然不能解决长时间序列的依赖问题。比如语音或文本识别中的长句子场景。 所以，这种有时间或顺序性的模型，是不能用几个分类器或学习模型串联起来进行等价的。 对于
相关文章
- 1. A Critical Review of Recurrent Neural Networks for Sequence Learning
- 2. 论文阅读：A Critical Review of Recurrent Neural Networks for Sequence Learning
- 3. 论文解读A Critical Review od Recurrent Neural Networks for Sequence Learning
- 4. Recurrent Neural Networks Tutorial阅读笔记
- 5. 《Graph Neural Networks: A Review of Methods and Applications》阅读笔记
- 6. Graph Neural Networks: A Review of Methods and Applications阅读笔记
- 7. Supervised Sequence Labelling with Recurrent Neural Networks 笔记 -LSTM
- 8. A Dual-Stage Attention-Based Recurrent Neural Network for Time Series Prediction阅读笔记
- 9. LSTM Recurrent Neural Networks for Short Text and Sentiment Classication文章阅读笔记
- 10. 【阅读笔记】《ReNet: A Recurrent Neural Network Based Alternative to Convolutional Networks》
- 更多相关文章...
- • RSS 阅读器 - RSS 教程
- • PHP 实例 - AJAX RSS 阅读器 - PHP教程
- • Tomcat学习笔记（史上最全tomcat学习笔记）
- • JDK13 GA发布：5大特性解读
相关标签/搜索
每日一句
-
每一个你不满意的现在，都有一个你没有努力的曾经。
欢迎关注本站公众号,获取更多信息
相关文章
- 1. A Critical Review of Recurrent Neural Networks for Sequence Learning
- 2. 论文阅读：A Critical Review of Recurrent Neural Networks for Sequence Learning
- 3. 论文解读A Critical Review od Recurrent Neural Networks for Sequence Learning
- 4. Recurrent Neural Networks Tutorial阅读笔记
- 5. 《Graph Neural Networks: A Review of Methods and Applications》阅读笔记
- 6. Graph Neural Networks: A Review of Methods and Applications阅读笔记
- 7. Supervised Sequence Labelling with Recurrent Neural Networks 笔记 -LSTM
- 8. A Dual-Stage Attention-Based Recurrent Neural Network for Time Series Prediction阅读笔记
- 9. LSTM Recurrent Neural Networks for Short Text and Sentiment Classication文章阅读笔记
- 10. 【阅读笔记】《ReNet: A Recurrent Neural Network Based Alternative to Convolutional Networks》