| Combating noisy labels by agreement: A joint training method with co-regularization. H Wei, L Feng, X Chen, B An Computer Vision and Pattern Recognition (CVPR), 13726-13735, 2020 | 670 | 2020 |
| Mitigating Neural Network Overconfidence with Logit Normalization H Wei, R Xie, H Cheng, L Feng, B An, Y Li International Conference on Machine Learning (ICML), 2022 | 324 | 2022 |
| Open-set Label Noise Can Improve Robustness Against Inherent Label Noise H Wei, L Tao, R Xie, B An Advances in Neural Information Processing Systems (NeurIPS), 2021 | 94 | 2021 |
| Commission fee is not enough: A hierarchical reinforced framework for portfolio management R Wang, H Wei, B An, Z Feng, J Yao Proceedings of the AAAI Conference on Artificial Intelligence 35 (1), 626-633, 2021 | 56* | 2021 |
| Open-Sampling: Exploring Out-of-Distribution data for Re-balancing Long-tailed datasets H Wei, L Tao, R Xie, L Feng, B An International Conference on Machine Learning (ICML), 2022 | 43 | 2022 |
| ACIL: Analytic Class-Incremental Learning with Absolute Memorization and Privacy Protection H Zhuang, Z Weng, H Wei, R Xie, KA Toh, Z Lin arXiv preprint arXiv:2205.14922, 2022 | 41 | 2022 |
| Mitigating Memorization of Noisy Labels by Clipping the Model Prediction H Wei, H Zhuang, R Xie, L Feng, G Niu, B An, Y Li International Conference on Machine Learning (ICML), 2023 | 35* | 2023 |
| Deep learning from multiple noisy annotators as a union H Wei, R Xie, L Feng, B Han, B An IEEE transactions on neural networks and learning systems 34 (12), 10552-10562, 2022 | 32 | 2022 |
| Conformal Prediction for Deep Classifier via Label Ranking J Huang, H Xi, L Zhang, H Yao, Y Qiu, H Wei ICML 2024, 2023 | 22 | 2023 |
| Understanding and Mitigating the Label Noise in Pre-training on Downstream Tasks H Chen, J Wang, A Shah, R Tao, H Wei, X Xie, M Sugiyama, B Raj ICML 2024, 2023 | 22 | 2023 |
| In defense of softmax parametrization for calibrated and consistent learning to defer Y Cao, H Mozannar, L Feng, H Wei, B An NeurIPS 2023, 2024 | 19 | 2024 |
| Dos: Diverse outlier sampling for out-of-distribution detection W Jiang, H Cheng, M Chen, C Wang, H Wei ICLR 2024, 2023 | 16 | 2023 |
| Can adversarial training be manipulated by non-robust features? L Tao, L Feng, H Wei, J Yi, SJ Huang, S Chen Advances in Neural Information Processing Systems 35, 26504-26518, 2022 | 15 | 2022 |
| Multiple-instance learning from similar and dissimilar bags L Feng, S Shu, Y Cao, L Tao, H Wei, T Xiang, B An, G Niu proceedings of the 27th ACM SIGKDD conference on knowledge discovery & data …, 2021 | 15 | 2021 |
| On the Importance of Feature Separability in Predicting Out-Of-Distribution Error R Xie, H Wei, Y Cao, L Feng, B An NeurIPS 2023, 2023 | 14 | 2023 |
| GearNet: Stepwise Dual Learning for Weakly Supervised Domain Adaptation R Xie, H Wei, L Feng, B An Proceedings of the AAAI Conference on Artificial Intelligence, 2022 | 13 | 2022 |
| Regression with cost-based rejection X Cheng, Y Cao, H Wang, H Wei, B An, L Feng NeurIPS 2023, 2024 | 9 | 2024 |
| Refined Coreset Selection: Towards Minimal Coreset Size under Model Performance Constraints X Xia, J Liu, S Zhang, Q Wu, H Wei, T Liu ICML 2024, 2024 | 9 | 2024 |
| Open-vocabulary calibration for fine-tuned CLIP S Wang, J Wang, G Wang, B Zhang, K Zhou, H Wei arXiv preprint arXiv:2402.04655, 2024 | 8* | 2024 |
| Optimization-free test-time adaptation for cross-person activity recognition S Wang, J Wang, H Xi, B Zhang, L Zhang, H Wei Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous …, 2024 | 8 | 2024 |
Lei FengProfessor, Southeast UniversityПодтвержден адрес электронной почты в домене seu.edu.cn