论文解析：NASE: Learning Knowledge Graph Embedding for Link Prediction via Neural Architecture Search
论文解析（CIKM 2020） NASE: Learning Knowledge Graph Embedding for Link Prediction via Neural Architecture Search 链接：https://arxiv.org/pdf/2008.07723.pdf 研究背景： 现有的知识图谱大多是不完整，且存在噪声，构建一个完备的知识图谱需要耗费大量的计算资源和存储空
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相关文章
- 1. NASE Learning Knowledge Graph Embedding for Link Prediction via Neural Architecture Search 阅读笔记
- 2. 论文笔记：AAAI 2020 Learning Hierarchy-Aware Knowledge Graph Embeddings for Link Prediction
- 3. Neural architecture search
- 4. RKGE Recurrent Knowledge Graph Embedding for Effective Recommendation 论文
- 5. Graph Few-shot learning via Knowledge Transfer
- 6. Research Guide for Neural Architecture Search
- 7. 论文笔记——NEURAL ARCHITECTURE SEARCH WITH REINFORCEMENT LEARNING
- 8. 论文笔记《Neural Architecture Search With Reinforcement Learning》
- 9. Neural Architecture Search with Reinforcement Learning论文总结
- 10. Efficient Neural Architecture Search via Parameter Sharing