Graph embedding-based heterogeneous domain adaptation with domain-invariant feature learning and distributional order preserving

Author:

Wang WenxuORCID,Li Zhenbo,Li WeiranORCID

Funder

National Key Research and Development Program of China

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience

Reference39 articles.

1. Amini, M., Usunier, N., & Goutte, C. (2009). Learning from Multiple Partially Observed Views - an Application to Multilingual Text Categorization. In NIPS (pp. 28–36).

2. Chua, T., Tang, J., Hong, R., Li, H., Luo, Z., & Zheng, Y. (2009). NUS-WIDE: A real-world web image database from National University of Singapore. In CIVR.

3. Deng, J., Dong, W., Socher, R., Li, L., Li, K., & Fei-Fei, L. (2009). ImageNet: A large-scale hierarchical image database. In CVPR (pp. 248–255).

4. Duan, L., Xu, D., & Tsang, I. W. (2012). Learning with Augmented Features for Heterogeneous Domain Adaptation. In ICML.

5. A discriminative feature mapping approach to heterogeneous domain adaptation;Fang;Pattern Recognition Letters,2018

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