Learning Transferable Features with Deep Adaptation Networks
本篇是迁移学习专栏介绍的第七篇论文，清华大学助理教授Mingsheng Long (龙明盛)发表在国际机器学习顶级会议JMLR 2015上的深度适配网络(Deep Adaptation Network, DAN)。前作DDC：Deep domain confusion: Maximizing for domain invariance DAN是在DDC的基础上发展起来的，它很好地解决了DDC的两个
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相关文章
- 1. Learning Transferable Features with Deep Adaptation Networks
- 2. 翻译“Learning Transferable Features with Deep Adaptation Networks”
- 3. 对于DAN方法的解读-Learning Transferable Features with Deep Adaptation Networks
- 4. How transferable are features in deep nerual networks? 【paper review】
- 5. How transferable are features in deep neural networks?
- 6. Dense biased networks with deep priori anatomy and hard region adaptation: Semi-supervised learning
- 7. M-ADDA: Unsupervised Domain Adaptation with Deep Metric Learning
- 8. How transferable are features in deep neural networks? 论文笔记
- 9. 论文笔记：How transferable are features in deep neural networks?
- 10. Unsupervised Domain Adaptation with Residual Transfer Networks（2017）