Unsupervised Domain Adaptation by Backpropagation(2015)
Introduction 论文作者希望网络学习由discriminativeness（分歧，应该是source domain和target domain的区别吧）和domain-invariance组合起来的隐藏特征（underlying feature） 通过同时优化以下两个discriminative classifiers来实现 label predictor预测分类标签（训练与测试的时候）
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- 2. 论文笔记 ——《Unsupervised Domain Adaptation by Backpropagation》
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相关文章
- 1. 论文笔记：Unsupervised Domain Adaptation by Backpropagation
- 2. 论文笔记 ——《Unsupervised Domain Adaptation by Backpropagation》
- 3. Unsupervised Domain Adaptation by Backpropagation(2015)学习总结
- 4. Unsupervised Domain Adaptation by Backpropagation(2015)学习笔记
- 5. Maximum Classifier Discrepancy for Unsupervised Domain Adaptation
- 6. Geodesic flow kernel for unsupervised domain adaptation
- 7. [MICCAI2019]Unsupervised Domain Adaptation via Disentangled Representations
- 8. Re-weighted adversarial adaptation network for unsupervised domain adaptation
- 9. DANN：Unsupervised Domain Adaptation by Backpropagation
- 10. Unsupervised domain adaptation with residual transfer networks(NIPS 2016)