《Convolutional Neural Networks for Sentence Classification》
《Convolutional Neural Networks for Sentence Classification》 概述：使用基於word2vec的單層CNN，對多個文本分類任務進行了評測。 結論： 1.word2vec是個好東西。使用pre-training 訓練的資源成爲nlp不可或缺的一部分。 2.Dropout可以提高2%-4%的相對性能。 3.多通道的CNN相對於Static CNN
相關文章
- 1. Convolutional Neural Networks for Sentence Classification
- 2. 論文《Convolutional Neural Networks for Sentence Classification》總結
- 3. 論文閱讀：《Convolutional Neural Networks for Sentence Classification》
- 4. 《Convolutional Neural Networks for Sentence Classification》論文研讀
- 5. Convolutional Neural Networks for Sentence Classification 閱讀筆記
- 6. Convolutional Neural Networks for Sentence Classification（閱讀理解）
- 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
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相關文章
- 1. Convolutional Neural Networks for Sentence Classification
- 2. 論文《Convolutional Neural Networks for Sentence Classification》總結
- 3. 論文閱讀：《Convolutional Neural Networks for Sentence Classification》
- 4. 《Convolutional Neural Networks for Sentence Classification》論文研讀
- 5. Convolutional Neural Networks for Sentence Classification 閱讀筆記
- 6. Convolutional Neural Networks for Sentence Classification（閱讀理解）
- 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