| Characterizing adversarial subspaces using local intrinsic dimensionality X Ma, B Li, Y Wang, SM Erfani, S Wijewickrema, ME Houle, ... ICLR2018, 2018 | 130 | 2018 |
| Dimensionality-Driven Learning with Noisy Labels X Ma, Y Wang, ME Houle, S Zhou, SM Erfani, ST Xia, S Wijewickrema, ... ICML2018, 2018 | 63 | 2018 |
| Iterative Learning with Open-set Noisy Labels Y Wang, W Liu, X Ma, J Bailey, H Zha, L Song, ST Xia CVPR2018, 2018 | 52 | 2018 |
| Residual convolutional CTC networks for automatic speech recognition Y Wang, X Deng, S Pu, Z Huang arXiv preprint arXiv:1702.07793, 2017 | 35 | 2017 |
| Decoupled networks W Liu, Z Liu, Z Yu, B Dai, R Lin, Y Wang, JM Rehg, L Song CVPR2018, 2771-2779, 2018 | 14 | 2018 |
| A novel consistent random forest framework: Bernoulli random forests Y Wang, ST Xia, Q Tang, J Wu, X Zhu IEEE Transactions on Neural Networks and Learning Systems 29 (8), 3510-3523, 2017 | 12 | 2017 |
| A less-greedy two-term Tsallis Entropy Information Metric approach for decision tree classification Y Wang, ST Xia, J Wu Knowledge-Based Systems 120, 34-42, 2017 | 12 | 2017 |
| Unifying attribute splitting criteria of decision trees by Tsallis entropy Y Wang, ST Xia ICASSP: 2017 IEEE International Conference on Acoustics, Speech and Signal …, 2017 | 12* | 2017 |
| Collaborative representation cascade for single-image super-resolution Y Zhang, Y Zhang, J Zhang, D Xu, Y Fu, Y Wang, X Ji, Q Dai IEEE Transactions on Systems, Man, and Cybernetics: Systems 49 (5), 845-860, 2017 | 11 | 2017 |
| On the Convergence and Robustness of Adversarial Training Y Wang, X Ma, J Bailey, J Yi, B Zhou, Q Gu ICML2019, 6586-6595, 2019 | 9 | 2019 |
| Bernoulli random forests: Closing the gap between theoretical consistency and empirical soundness W Yisen, T Qingtao, ST Xia, J Wu, X Zhu IJCAI: International Joint Conference on Artificial Intelligence, 2016 | 8 | 2016 |
| End-to-end coding for TCP Yong Cui, Lian Wang, Xin Wang, Yisen Wang, Fengyuan Ren, Shu-Tao Xia IEEE Network 30 (2), 68-73, 2016 | 8* | 2016 |
| A generic denoising framework via guided principal component analysis T Dai, Z Xu, H Liang, K Gu, Q Tang, Y Wang, W Lu, ST Xia Journal of Visual Communication and Image Representation 48, 340-352, 2017 | 7 | 2017 |
| Link sign prediction by variational bayesian probabilistic matrix factorization with student-t prior Y Wang, F Liu, ST Xia, J Wu Information Sciences 405, 175-189, 2017 | 7 | 2017 |
| Student-t Process Regression with dependent Student-t noise Q Tang, Y Wang, ST Xia ECAI 2016: 22nd European Conference on Artificial Intelligence, 29 August-2 …, 2016 | 7 | 2016 |
| A novel feature subspace selection method in random forests for high dimensional data Y Wang, ST Xia 2016 International Joint Conference on Neural Networks (IJCNN), 4383-4389, 2016 | 6 | 2016 |
| Unbiased Multivariate Correlation Analysis Y Wang, S Romano, V Nguyen, J Bailey, X Ma, ST Xia AAAI: Proceedings of the Thirty-First AAAI Conference on Artificial …, 2017 | 5 | 2017 |
| Symmetric cross entropy for robust learning with noisy labels Y Wang, X Ma, Z Chen, Y Luo, J Yi, J Bailey ICCV, 322-330, 2019 | 4 | 2019 |
| Improving decision trees by Tsallis Entropy Information Metric method Y Wang, C Song, ST Xia 2016 International Joint Conference on Neural Networks (IJCNN), 4729-4734, 2016 | 4 | 2016 |
| Learning deep hidden nonlinear dynamics from aggregate data Y Wang, B Dai, L Kong, X Ma, SM Erfani, J Bailey, ST Xia, L Song, H Zha UAI2018, 2018 | 3 | 2018 |
Shu-Tao XiaTsinghua UniversityVerified email at sz.tsinghua.edu.cn
