《Convolutional Neural Networks for Sentence Classification》
《Convolutional Neural Networks for Sentence Classification》 概述：使用基于word2vec的单层CNN，对多个文本分类任务进行了评测。 结论： 1.word2vec是个好东西。使用pre-training 训练的资源成为nlp不可或缺的一部分。 2.Dropout可以提高2%-4%的相对性能。 3.多通道的CNN相对于Static CNN
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- 1. Convolutional Neural Networks for Sentence Classification
- 2. 论文《Convolutional Neural Networks for Sentence Classification》总结
- 3. 论文阅读：《Convolutional Neural Networks for Sentence Classification》
- 4. 《Convolutional Neural Networks for Sentence Classification》论文研读
- 5. Convolutional Neural Networks for Sentence Classification 阅读笔记
- 6. Convolutional Neural Networks for Sentence Classification（阅读理解）
- 7. [NLP-CNN] Convolutional Neural Networks for Sentence Classification -2014-EMNLP
- 8. 【Paper】TextCNN：Convolutional Neural Networks for Sentence Classification
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相关文章
- 1. Convolutional Neural Networks for Sentence Classification
- 2. 论文《Convolutional Neural Networks for Sentence Classification》总结
- 3. 论文阅读：《Convolutional Neural Networks for Sentence Classification》
- 4. 《Convolutional Neural Networks for Sentence Classification》论文研读
- 5. Convolutional Neural Networks for Sentence Classification 阅读笔记
- 6. Convolutional Neural Networks for Sentence Classification（阅读理解）
- 7. [NLP-CNN] Convolutional Neural Networks for Sentence Classification -2014-EMNLP
- 8. 【Paper】TextCNN：Convolutional Neural Networks for Sentence Classification
- 9. Convolutional Neural Network For Sentence Classification
- 10. Recurrent Convolutional Neural Networks for Text Classification