論文筆記：Hybrid Attention-Based Prototypical Networks for Noisy Few-Shot Relation Classification
基本信息 github：地址 會議：2019 AAAI 標籤：關係抽取、小樣本 筆記 1. 整體思路是什麼？ 問題設定：小樣本關係抽取，N way K shot 的任務。 數據集：FewRel 1.0數據集，在數據集中引入了 （錯誤標註的情況） 出發點：在小樣本中噪聲數據對模型影響是巨大的。小樣本學到的特徵是稀疏的。 方式：小樣本學習中的metric learning方法，用了之前Prototyp
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相關文章
- 1. Hybrid Attention-Based Prototypical Networks for Noisy Few-Shot Relation Classification （2019 AAAI）
- 2. 論文筆記：Prototypical Networks for Few-shot Learning
- 3. 論文筆記--Appearance-and-Relation Networks for Video Classification
- 4. 論文筆記：Relation Networks for Object Detection
- 5. Reinforcement Learning for Relation Classification from Noisy Data
- 6. 論文閱讀 Prototypical Networks for Few-shot Learning
- 7. prototypical networks for few-shot learning論文
- 8. Appearance-and-Relation Networks for Video Classification
- 9. Reinforcement Learning for Relation Classification from Noisy Data閱讀筆記
- 10. 論文閱讀筆記 Prototypical Networks for Few-shot Learning