| Weighted linear loss multiple birth support vector machine based on information granulation for multi-class classification S Ding, X Zhang, Y An, Y Xue Pattern Recognition 67, 32-46, 2017 | 78 | 2017 |
| Wavelet twin support vector machines based on glowworm swarm optimization S Ding, Y An, X Zhang, F Wu, Y Xue Neurocomputing 225, 157-163, 2017 | 73 | 2017 |
| Discrete space reinforcement learning algorithm based on support vector machine classification Y An, S Ding, S Shi, J Li Pattern Recognition Letters 111, 30-35, 2018 | 38 | 2018 |
| Survey on multi-class twin support vector machines S Ding, J Zhang, X Zhang, Y An Journal of Software 29 (1), 89-108, 2018 | 37* | 2018 |
| Asynchronous reinforcement learning algorithms for solving discrete space path planning problems X Zhao, S Ding, Y An, W Jia Applied Intelligence 48, 4889-4904, 2018 | 32 | 2018 |
| Conditional Self-Supervised Learning for Few-Shot Classification Y An, H Xue, X Zhao, L Zhang International Joint Conference on Artificial Intelligence (IJCAI'21), 2140-2146, 2021 | 28 | 2021 |
| Applications of asynchronous deep reinforcement learning based on dynamic updating weights X Zhao, S Ding, Y An, W Jia Applied Intelligence 49, 581-591, 2019 | 20 | 2019 |
| Indefinite twin support vector machine with DC functions programming Y An, H Xue Pattern Recognition 121, 108195, 2022 | 16 | 2022 |
| Multiple birth support vector machine based on recurrent neural networks S Ding, Y Sun, Y An, W Jia Applied Intelligence 50, 2280-2292, 2020 | 15 | 2020 |
| Fusion Label Enhancement for Multi-Label Learning X Zhao, Y An, N Xu, X Geng International Joint Conference on Artificial Intelligence (IJCAI'22), 3773-3779, 2022 | 9 | 2022 |
| Continuous label distribution learning X Zhao, Y An, N Xu, X Geng Pattern Recognition 133, 109056, 2023 | 7 | 2023 |
| From instance to metric calibration: A unified framework for open-world few-shot learning Y An, H Xue, X Zhao, J Wang IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023 | 6 | 2023 |
| Imbalanced label distribution learning X Zhao, Y An, N Xu, J Wang, X Geng Proceedings of the AAAI Conference on Artificial Intelligence 37 (9), 11336 …, 2023 | 5 | 2023 |
| A new asynchronous architecture for tabular reinforcement learning algorithms X Zhao, S Ding, Y An Proceedings of ELM-2017, 172-180, 2019 | 3 | 2019 |
| Variational Continuous Label Distribution Learning for Multi-Label Text Classification X Zhao, Y An, N Xu, X Geng IEEE Transactions on Knowledge and Data Engineering, 2023 | 2 | 2023 |
| Multiple Birth Support Vector Machine with Triplet Loss Function. SF Ding, YX An Journal of Information Science & Engineering 35 (6), 1365-1376, 2019 | 2 | 2019 |
| Generalizable Label Distribution Learning X Zhao, L Qi, Y An, X Geng Proceedings of the 31st ACM International Conference on Multimedia, 8932-8941, 2023 | 1 | 2023 |
| Boosting Few-Shot Open-Set Recognition with Multi-Relation Margin Loss Y Che, Y An, H Xue International Joint Conference on Artificial Intelligence (IJCAI'23), 0 | 1* | |
| Learning to Learn from Corrupted Data for Few-Shot Learning Y An, X Zhao, H Xue International Joint Conference on Artificial Intelligence (IJCAI'23), 0 | 1* | |
| Reinforced Self-Supervised Training for Few-Shot Learning Z Yan, Y An, H Xue IEEE Signal Processing Letters, 2024 | | 2024 |
Hui XueSoutheast University
