Transductive Unbiased Embedding for Zero-Shot Learning閱讀筆記
Transductive Unbiased Embedding for Zero-Shot Learning Summary PRO ubias term: 在Loss添加一個針對未知類的loss, 部分抑制了zero shot天生傾向於帶label數據的問題 巧妙的數據利用，雖然target dataset沒有用label(圖片文字對應關係)，但是用了label的文字embedding 對CNN
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- 1. [CVPR 18] Transductive Unbiased Embedding for Zero-Shot Learning
- 2. 【論文學習筆記】Transductive Unbiased Embedding for Zero-Shot Learning (2018_CVPR)
- 3. 論文閱讀筆記《Learning Embedding Adaptation for Few-Shot Learning》
- 4. 論文閱讀筆記《Transductive Episodic-Wise Adaptive Metric for Few-Shot Learning》
- 5. 論文閱讀筆記《Learning to propagate labels: Transductive propagation network for few-shot learning》
- 6. FeUdal Networks for Hierarchical Reinforcement Learning 閱讀筆記
- 7. 論文閱讀筆記《Instance-Level Embedding Adaptation for Few-Shot Learning》
- 8. NASE Learning Knowledge Graph Embedding for Link Prediction via Neural Architecture Search 閱讀筆記
- 9. Transfer Learning in a Transductive Setting閱讀筆記NIPS2013
- 10. Matching Networks for one Shot Learning 閱讀筆記
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相關文章
- 1. [CVPR 18] Transductive Unbiased Embedding for Zero-Shot Learning
- 2. 【論文學習筆記】Transductive Unbiased Embedding for Zero-Shot Learning (2018_CVPR)
- 3. 論文閱讀筆記《Learning Embedding Adaptation for Few-Shot Learning》
- 4. 論文閱讀筆記《Transductive Episodic-Wise Adaptive Metric for Few-Shot Learning》
- 5. 論文閱讀筆記《Learning to propagate labels: Transductive propagation network for few-shot learning》
- 6. FeUdal Networks for Hierarchical Reinforcement Learning 閱讀筆記
- 7. 論文閱讀筆記《Instance-Level Embedding Adaptation for Few-Shot Learning》
- 8. NASE Learning Knowledge Graph Embedding for Link Prediction via Neural Architecture Search 閱讀筆記
- 9. Transfer Learning in a Transductive Setting閱讀筆記NIPS2013
- 10. Matching Networks for one Shot Learning 閱讀筆記