| Consistency and diversity neural network multi-view multi-label learning D Zhao, Q Gao, Y Lu, D Sun, Y Cheng Knowledge-Based Systems 218, 106841, 2021 | 72 | 2021 |
| Multi-label learning with kernel extreme learning machine autoencoder Y Cheng, D Zhao, Y Wang, G Pei Knowledge-Based Systems 178, 1-10, 2019 | 53 | 2019 |
| Weight matrix sharing for multi-label learning K Qian, XY Min, Y Cheng, F Min Pattern Recognition 136, 109156, 2023 | 41 | 2023 |
| Joint label completion and label-specific features for multi-label learning algorithm Y Wang, W Zheng, Y Cheng, D Zhao Soft Computing 24 (9), 6553-6569, 2020 | 37 | 2020 |
| Missing multi-label learning with non-equilibrium based on classification margin Y Cheng, K Qian, Y Wang, D Zhao Applied Soft Computing 86, 105924, 2020 | 28 | 2020 |
| Global and local attention-based multi-label learning with missing labels Y Cheng, K Qian, F Min Information Sciences 594, 20-42, 2022 | 20 | 2022 |
| Two-level label recovery-based label embedding for multi-label classification with missing labels Y Wang, W Zheng, Y Cheng, D Zhao Applied Soft Computing 99, 106868, 2021 | 17 | 2021 |
| Apriori 算法中频繁项集挖掘实现研究 程玉胜， 邓小光， 江效尧 计算机技术与发展 16 (3), 58-60, 2006 | 17 | 2006 |
| Self-dependence multi-label learning with double k for missing labels K Qian, XY Min, Y Cheng, G Song, F Min Artificial Intelligence Review 56 (6), 5057-5094, 2023 | 14 | 2023 |
| Multi-label learning of non-equilibrium labels completion with mean shift C Yusheng, Z Dawei, Z Wenfa, W Yibin Neurocomputing 321, 92-102, 2018 | 14 | 2018 |
| Automatic determination about precision parameter value based on inclusion degree with variable precision rough set model Y Cheng, W Zhan, X Wu, Y Zhang Information Sciences 290, 72-85, 2015 | 14 | 2015 |
| Asymmetry label correlation for multi-label learning J Bao, Y Wang, Y Cheng Applied Intelligence 52 (6), 6093-6105, 2022 | 13 | 2022 |
| 基于边界域的知识粗糙熵与粗集粗糙熵 程玉胜， 张佑生， 胡学钢 系统仿真学报 19 (9), 2008-2011, 2007 | 13 | 2007 |
| Streaming Feature Selection for Multi-Label Data with Dynamic Sliding Windows and Feature Repulsion Loss YLIY CHENG https://doi.org/10.3390/e21121151 21 (12), 2019 | 12* | 2019 |
| Multi-view multi-label learning with view feature attention allocation Y Cheng, Q Li, Y Wang, W Zheng Neurocomputing 501, 857-874, 2022 | 11 | 2022 |
| Rosetta 实验系统在机器学习中的应用 程玉胜 安庆师范学院学报: 自然科学版 11 (2), 69-72, 2005 | 11 | 2005 |
| Parallel dual-channel multi-label feature selection J Miao, Y Wang, Y Cheng, F Chen Soft Computing 27 (11), 7115-7130, 2023 | 10 | 2023 |
| Multi-label space reshape for semantic-rich label-specific features learning Y Cheng, C Zhang, S Pang International Journal of Machine Learning and Cybernetics 13 (4), 1005-1019, 2022 | 10 | 2022 |
| 不完备信息系统的属性约简方法研究 程玉胜， 胡学钢， 江效尧 计算机工程与应用 40 (1), 68-70, 2004 | 10 | 2004 |
| The relationships between variable precision value and knowledge reduction based on variable precision rough set model C Yusheng, Z Yousheng, H Xuegang RSKT2006, Berlin: Springer-Verlag, Lecture Notes in Computer Science (to appear), 2006 | 9 | 2006 |
