Graph Few-shot learning via Knowledge Transfer
Preliminaries 圖神經網絡 一個圖 G \mathcal{G} G由其鄰接矩陣和節點特徵 ( A , X ) (\mathbf{A},\mathbf{X}) (A,X)表示，其中 A ∈ { 0 , 1 } n × n \mathbf{A} \in\{0,1\}^{n \times n} A∈{0,1}n×n, X = { x 1 , … , x n } ∈ R n × h \math
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相關文章
- 1. Transfer Learning for Item Recommendations and Knowledge Graph Completion
- 2. (13)[ICLR16] Net2Net: ACCELERATING LEARNING VIA KNOWLEDGE TRANSFER
- 3. Graphonomy: Universal Human Parsing via Graph Transfer Learning
- 4. 閱讀理解《Better and Faster: Knowledge Transfer from Multiple Self-supervised Learning Tasks via Graph D》
- 5. Paper Note --- Transfer Learning via Dimensionality Reduction
- 6. 論文解析：NASE: Learning Knowledge Graph Embedding for Link Prediction via Neural Architecture Search
- 7. NASE Learning Knowledge Graph Embedding for Link Prediction via Neural Architecture Search 閱讀筆記
- 8. Unifying Task-oriented Knowledge Graph Learning and Recommendation
- 9. 遷移學習論文閱讀：Transfer Learning via Learning to Transfer
- 10. 【distill.&transfer】Deep Face Recognition Model Compression via Knowledge Transfer and Distillation