關於《Domain Adaptation with Adversarial Training and Graph Embeddings》的理解
使用對抗學習和圖像嵌入的域適應學習 本文將基於對抗學習和圖像嵌入的域適應運用於危機狀態下的輿情分析，主要處理的前提是：源域有labeled的數據和unlabeled的數據，而目標域unlabeled。模型則包含基於域適應的對抗學習和基於圖像的半監督學習。數據來源是 two real-world crisis datasets collected from Twitter。 作者做這個模型的立意是爲
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相關文章
- 1. [論文翻譯]Intramodality Domain Adaptation Using Self Ensembling and Adversarial Training
- 2. Multi-Adversarial Domain Adaptation
- 3. [cvpr2017]Adversarial Discriminative Domain Adaptation
- 4. [cvpr2017]Unsupervised Pixel–Level Domain Adaptation with Generative Adversarial Networks
- 5. ADDA: Adversarial Discriminative Domain Adaptation
- 6. Re-weighted adversarial adaptation network for unsupervised domain adaptation
- 7. KBGAN: Adversarial Learning for Knowledge Graph Embeddings理解
- 8. Domain Adaptation 與 Generative Adversarial Network
- 9. 【Transfer Learning】Adversarial Discriminative Domain Adaptation
- 10. Domain-Adversarial Training of Neural Networks