17.Interpretable Adversarial Perturbation in Input Embedding Space for Text
該文章對本人博客論文5.Adversarial Training Methods for Semi-Supervised Text Classification做了進一步的解釋實驗。 論文5針對NLP中半監督問題提出瞭解決的方案。 1.對抗訓練是一種數劇增強的方法 ，即在原數據基礎上求其一個最大的擾動，得到其對抗樣本。 2.虛擬對抗是針對半監督學習，對於沒有標籤的那一部分，根據KL散度，生成其對抗
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相關文章
- 1. 【深度學習NLP論文筆記】《Interpretable Adversarial Perturbation in Input Embedding Space for Text》
- 2. [Space Geodesy] Perturbation Theory
- 3. Adversarial Multi-task Learning for Text Classification
- 4. [解讀] ClusterGAN : Latent Space Clustering in Generative Adversarial Networks
- 5. A Robust Adversarial Training Approach to Machine Reading Comprehension
- 6. 讀書筆記17：Adversarial Attacks on Neural Networks for Graph Data
- 7. Generative Adversarial Text to Image Synthesis
- 8. [轉] Implementing a CNN for Text Classification in TensorFlow
- 9. A NEW METHOD OF REGION EMBEDDING FOR TEXT CLASSIFICATION
- 10. 30 Examples For Awk Command In Text Processing