| Instance-dependent partial label learning N Xu, C Qiao, X Geng, ML Zhang Advances in Neural Information Processing Systems 34, 27119-27130, 2021 | 65 | 2021 |
| Aim 2020 challenge on rendering realistic bokeh A Ignatov, R Timofte, M Qian, C Qiao, J Lin, Z Guo, C Li, C Leng, J Cheng, ... Computer Vision–ECCV 2020 Workshops: Glasgow, UK, August 23–28, 2020 …, 2020 | 43 | 2020 |
| Bggan: Bokeh-glass generative adversarial network for rendering realistic bokeh M Qian, C Qiao, J Lin, Z Guo, C Li, C Leng, J Cheng Computer Vision–ECCV 2020 Workshops: Glasgow, UK, August 23–28, 2020 …, 2020 | 28 | 2020 |
| One positive label is sufficient: Single-positive multi-label learning with label enhancement N Xu, C Qiao, J Lv, X Geng, ML Zhang Advances in Neural Information Processing Systems 35, 21765-21776, 2022 | 23 | 2022 |
| Decompositional generation process for instance-dependent partial label learning C Qiao, N Xu, X Geng arXiv preprint arXiv:2204.03845, 2022 | 11 | 2022 |
| Progressive purification for instance-dependent partial label learning N Xu, B Liu, J Lv, C Qiao, X Geng International Conference on Machine Learning, 38551-38565, 2023 | 9 | 2023 |
| Multi-View Partial Multi-Label Learning via Graph-Fusion-Based Label Enhancement N Xu, YD Wu, C Qiao, Y Ren, M Zhang, X Geng IEEE Transactions on Knowledge and Data Engineering, 2022 | 4 | 2022 |
| Fredis: A fusion framework of refinement and disambiguation for unreliable partial label learning C Qiao, N Xu, J Lv, Y Ren, X Geng International Conference on Machine Learning, 28321-28336, 2023 | 1 | 2023 |
| Variational Label-Correlation Enhancement for Congestion Prediction B Liu, C Qiao, N Xu, X Geng, Z Zhu, J Yang 2024 29th Asia and South Pacific Design Automation Conference (ASP-DAC), 466-471, 2024 | | 2024 |
Ning XuSchool of Computer Science and Engineering, Southeast University, ChinaVerified email at seu.edu.cn
