| Collaboration based multi-label learning L Feng, B An, S He Proceedings of the AAAI conference on artificial intelligence 33 (01), 3550-3557, 2019 | 68 | 2019 |
| Discriminatively relabel for partial multi-label learning S He, K Deng, L Li, S Shu, L Liu 2019 IEEE International Conference on Data Mining (ICDM), 280-288, 2019 | 19 | 2019 |
| Incorporating multiple cluster centers for multi-label learning S Shu, F Lv, Y Yan, L Li, S He, J He Information Sciences 590, 60-73, 2022 | 14 | 2022 |
| Estimating latent relative labeling importances for multi-label learning S He, L Feng, L Li 2018 IEEE International Conference on Data Mining (ICDM), 1013-1018, 2018 | 13 | 2018 |
| Partial label learning with semantic label representations S He, L Feng, F Lv, W Li, G Yang Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022 | 10 | 2022 |
| Candidate-aware selective disambiguation based on normalized entropy for instance-dependent partial-label learning S He, G Yang, L Feng Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 2 | 2023 |
| Candidate Label Set Pruning: A Data-centric Perspective for Deep Partial-label Learning S He, C Wang, G Yang, L Feng The Twelfth International Conference on Learning Representations, 0 | 1 | |
| BDetCLIP: Multimodal Prompting Contrastive Test-Time Backdoor Detection Y Niu, S He, Q Wei, F Liu, L Feng arXiv preprint arXiv:2405.15269, 2024 | | 2024 |
| Partial-label Learning with Mixed Closed-set and Open-set Out-of-candidate Examples S He, L Feng, G Yang Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023 | | 2023 |
| A generalized unbiased risk estimator for learning with augmented classes S Shu, S He, H Wang, H Wei, T Xiang, L Feng Proceedings of the AAAI Conference on Artificial Intelligence 37 (8), 9829-9836, 2023 | | 2023 |
Lei FengSingapore University of Technology and Design在 sutd.edu.sg 的电子邮件经过验证
