【論文筆記】SpotTune: Transfer Learning through Adaptive Fine-tuning
【CVPR2019】SpotTune: Transfer Learning through Adaptive Fine-tuning 論文鏈接：SpotTune: Transfer Learning through Adaptive Fine-tuning 一. Introduction 使用深度學習模型時，微調(fine-tune)是應用最普遍的遷移學習方法。它具體指先在源任務上獲得預
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相關文章
- 1. Towards Alzheimer’s Disease Classification through Transfer Learning
- 2. Text Style Transfer論文筆記
- 3. Transfer Learning[論文合集]
- 4. 論文筆記 —— 《A Survey on Transfer Learning》
- 5. Secure Federated Transfer Learning（論文筆記）
- 6. Visual Attribute Transfer through Deep Image Analogy論文閱讀筆記
- 7. Meta-Transfer Learning for Few-Shot Learning 論文筆記
- 8. 論文閱讀筆記《TADAM: Task dependent adaptive metric for improved few-shot learning》
- 9. 論文筆記12:Building Adaptive Tutoring Model using Artificial Neural Networks and Reinforcement Learning
- 10. （AM3）Adaptive Cross-Modal Few-shot Learning 論文筆記