| Tackling instance-dependent label noise via a universal probabilistic model Q Wang, B Han, T Liu, G Niu, J Yang, C Gong Thirty-Fifth AAAI Conference on Artificial Intelligence, 10192--10200, 2021 | 9 | 2021 |
| Probabilistic Margins for Instance Reweighting in Adversarial Training Q Wang, F Liu, B Han, T Liu, C Gong, G Niu, M Zhou, M Sugiyama 35th Conference on Neural Information Processing Systems, Sydney, Australia., 2021 | 5* | 2021 |
| Learning with group noise Q Wang, J Yao, C Gong, T Liu, M Gong, H Yang, B Han Thirty-Fifth AAAI Conference on Artificial Intelligence, 10192--10200, 2021 | 4 | 2021 |
| Instance-Dependent Positive and Unlabeled Learning with Labeling Bias Estimation C Gong, Q Wang, T Liu, B Han, JJ You, J Yang, D Tao IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021 | 3 | 2021 |
| Fraud Detection under Multi-Sourced Extremely Noisy Annotations C Zhang, Q Wang, T Liu, X Lu, J Hong, B Han, C Gong 30th ACM Int’l Conf. on Information and Knowledge Management (CIKM ’21 …, 2021 | 1 | 2021 |
