| Adaptive graph guided disambiguation for partial label learning DB Wang, ML Zhang, L Li IEEE TPAMI, 2022 | 112 | 2022 |
| Rethinking Calibration of Deep Neural Networks: Don't Be Afraid of Overconfidence DB Wang, L Feng, ML Zhang NeurIPS, 2021 | 91 | 2021 |
| Multi-View Multi-Label Learning with View-Specific Information Extraction. X Wu, QG Chen, Y Hu, D Wang, X Chang, X Wang, ML Zhang IJCAI, 2019 | 69 | 2019 |
| Revisiting Consistency Regularization for Deep Partial Label Learning DD Wu, DB Wang, ML Zhang ICML, 2022 | 49 | 2022 |
| Learning from Noisy Labels with Complementary Loss Functions DB Wang, Y Wen, L Pan, ML Zhang AAAI, 2021 | 26 | 2021 |
| Learning from Complementary Labels via Partial-Output Consistency Regularization DB Wang, L Feng, ML Zhang IJCAI, 2021 | 8 | 2021 |
| On the Pitfall of Mixup for Uncertainty Calibration DB Wang, L Li, P Zhao, PA Heng, ML Zhang CVPR, 2023 | 5 | 2023 |
| Learning from Noisy Labels via Dynamic Loss Thresholding H Yang, Y Jin, Z Li, DB Wang, L Miao, X Geng, ML Zhang IEEE TKDE, 2023 | 5 | 2023 |
| Multiple-Instance Learning from Triplet Comparison Bags S Shu, DB Wang, S Yuan, H Wei, J Jiang, L Feng, ML Zhang ACM TKDD, 2024 | 1 | 2024 |
| Partial-Label Regression X Cheng, D Wang, L Feng, M Zhang, B An AAAI, 2023 | 1 | 2023 |
| Partial Label Learning with Emerging New Labels XR Yu, DB Wang, ML Zhang Machine Learning, 1-17, 2022 | 1 | 2022 |
| Dimensionality Reduction for Partial Label Learning: A Unified and Adaptive Approach XR Yu, DB Wang, ML Zhang IEEE TKDE, 2024 | | 2024 |
| Student Loss: Towards the Probability Assumption in Inaccurate Supervision S Zhang, JQ Li, H Fujita, YW Li, DB Wang, TT Zhu, ML Zhang, CY Liu IEEE TPAMI, 2024 | | 2024 |
| Distilling Reliable Knowledge for Instance-dependent Partial Label Learning DD Wu, DB Wang, ML Zhang AAAI, 2024 | | 2024 |
Min-Ling ZhangProfessor, School of Computer Science and Engineering, Southeast University, ChinaVerified email at seu.edu.cn
