元图Meta-Graph: Few shot link prediction via meta learning理解与部分翻译
引言 链接预测的目的是能够从图中学习并推测出新的或者未知的关系。比如说，从社交网络方面，通过链接预测构建一个朋友推荐系统，从生物网络方面，通过链接预测推断出药物、蛋白质和疾病直接的关系。但是这些工作只聚焦于单一的问题设置：链接预测都用于一个单一的大图，并且这个图中的关系完整，至少有50%的真实链接（边）可以在训练阶段被看到。 本篇文章要做是基于小样本链接预测这么一个更有挑战性的设定，目标是在多个只
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相关文章
- 1. Meta-SGD: Learning to learn quickly for few shot learning---翻译理解
- 2. Few-shot Learning with Meta Metric Learners
- 3. Graph Few-shot learning via Knowledge Transfer
- 4. few-shot learning, zero-shot learning, one-shot learning,any-shot learning, C-way K-shot，Meta-learn
- 5. 小样本学习（Few-shot Learning）与元学习(meta-learning)初步
- 6. FEW-SHOT LEARNING WITH GRAPH NEURAL NETWORKS翻译
- 7. 翻译-Neural Snowball for Few-Shot Relation Learning
- 8. 元学习与小样本学习理解 Meta learning and Few shot learning
- 9. 【论文阅读】[meta learning]cross-domain few-shot classification via learned feature-wise transformation.
- 10. Few-shot Object Detection via Feature Reweighting