| Deep cocktail network: Multi-source unsupervised domain adaptation with category shift R Xu, Z Chen, W Zuo, J Yan, L Lin Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 39 | 2018 |
| Cost-effective object detection: Active sample mining with switchable selection criteria K Wang, L Lin, X Yan, Z Chen, D Zhang, L Zhang IEEE transactions on neural networks and learning systems 30 (3), 834-850, 2018 | 6 | 2018 |
| Graph neural reasoning for 2-quantified boolean formula solvers Z Yang, F Wang, Z Chen, G Wei, T Rompf arXiv preprint arXiv:1904.12084, 2019 | 4 | 2019 |
| Blending-target domain adaptation by adversarial meta-adaptation networks Z Chen, J Zhuang, X Liang, L Lin Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2019 | 3 | 2019 |
| Deep co-space: Sample mining across feature transformation for semi-supervised learning Z Chen, K Wang, X Wang, P Peng, E Izquierdo, L Lin IEEE Transactions on Circuits and Systems for Video Technology 28 (10), 2667 …, 2017 | 2 | 2017 |
| FRAME Revisited: An Interpretation View Based on Particle Evolution X Cai, Y Wu, G Li, Z Chen, L Lin Proceedings of the AAAI Conference on Artificial Intelligence 33, 3256-3263, 2019 | 1 | 2019 |
| Graph Neural Reasoning May Fail in Proving Boolean Unsatisfiability Z Chen, Z Yang arXiv preprint arXiv:1909.11588, 2019 | | 2019 |
| Multivariate-Information Adversarial Ensemble for Scalable Joint Distribution Matching Z Chen, Z Yang, X Wang, X Liang, X Yan, G Li, L Lin arXiv preprint arXiv:1907.03426, 2019 | | 2019 |
| Meta R-CNN: Towards General Solver for Instance-level Low-shot Learning X Yan, Z Chen, A Xu, X Wang, X Liang, L Lin Proceedings of the IEEE International Conference on Computer Vision, 9577-9586, 2019 | | 2019 |
| Supplementary Material for “Deep Cocktail Network: Multi-source Unsupervised Domain Adaptation with Category Shift” R Xu, Z Chen, W Zuo, J Yan, L Lin | | |
