论文笔记：Hybrid Attention-Based Prototypical Networks for Noisy Few-Shot Relation Classification
基本信息 github：地址 会议：2019 AAAI 标签：关系抽取、小样本 笔记 1. 整体思路是什么？ 问题设定：小样本关系抽取，N way K shot 的任务。 数据集：FewRel 1.0数据集，在数据集中引入了 （错误标注的情况） 出发点：在小样本中噪声数据对模型影响是巨大的。小样本学到的特征是稀疏的。 方式：小样本学习中的metric learning方法，用了之前Prototyp
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相关文章
- 1. Hybrid Attention-Based Prototypical Networks for Noisy Few-Shot Relation Classification （2019 AAAI）
- 2. 论文笔记：Prototypical Networks for Few-shot Learning
- 3. 论文笔记--Appearance-and-Relation Networks for Video Classification
- 4. 论文笔记：Relation Networks for Object Detection
- 5. Reinforcement Learning for Relation Classification from Noisy Data
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- 7. prototypical networks for few-shot learning论文
- 8. Appearance-and-Relation Networks for Video Classification
- 9. Reinforcement Learning for Relation Classification from Noisy Data阅读笔记
- 10. 论文阅读笔记 Prototypical Networks for Few-shot Learning