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| Multi-label feature selection based on max-dependency and min-redundancy Y Lin, Q Hu, J Liu, J Duan Neurocomputing 168, 92-103, 2015 | 227 | 2015 |
| Streaming feature selection for multilabel learning based on fuzzy mutual information Y Lin, Q Hu, J Liu, J Li, X Wu IEEE Transactions on Fuzzy Systems 25 (6), 1491-1507, 2017 | 156 | 2017 |
| Multi-label feature selection based on neighborhood mutual information Y Lin, Q Hu, J Liu, J Chen, J Duan Applied soft computing 38, 244-256, 2016 | 156 | 2016 |
| Learning to generalize unseen domains via memory-based multi-source meta-learning for person re-identification Y Zhao, Z Zhong, F Yang, Z Luo, Y Lin, S Li, N Sebe Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 136 | 2021 |
| Attribute reduction for multi-label learning with fuzzy rough set Y Lin, Y Li, C Wang, J Chen Knowledge-based systems 152, 51-61, 2018 | 130 | 2018 |
| Online multi-label streaming feature selection based on neighborhood rough set J Liu, Y Lin, Y Li, W Weng, S Wu Pattern Recognition 84, 273-287, 2018 | 119 | 2018 |
| An effective collaborative filtering algorithm based on user preference clustering J Zhang, Y Lin, M Lin, J Liu Applied Intelligence 45, 230-240, 2016 | 118 | 2016 |
| Feature selection using Fisher score and multilabel neighborhood rough sets for multilabel classification L Sun, T Wang, W Ding, J Xu, Y Lin Information Sciences 578, 887-912, 2021 | 103 | 2021 |
| Joint noise-tolerant learning and meta camera shift adaptation for unsupervised person re-identification F Yang, Z Zhong, Z Luo, Y Cai, Y Lin, S Li, N Sebe Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 103 | 2021 |
| Feature selection via neighborhood multi-granulation fusion Y Lin, J Li, P Lin, G Lin, J Chen Knowledge-Based Systems 67, 162-168, 2014 | 98 | 2014 |
| Multi-label learning with label-specific features by resolving label correlations J Zhang, C Li, D Cao, Y Lin, S Su, L Dai, S Li Knowledge-Based Systems 159, 148-157, 2018 | 95 | 2018 |
| Multi-label learning based on label-specific features and local pairwise label correlation W Weng, Y Lin, S Wu, Y Li, Y Kang Neurocomputing 273, 385-394, 2018 | 87 | 2018 |
| Feature selection based on quality of information J Liu, Y Lin, M Lin, S Wu, J Zhang Neurocomputing 225, 11-22, 2017 | 80 | 2017 |
| Multi-label feature selection with streaming labels Y Lin, Q Hu, J Zhang, X Wu Information Sciences 372, 256-275, 2016 | 79 | 2016 |
| A graph approach for fuzzy-rough feature selection J Chen, J Mi, Y Lin Fuzzy Sets and Systems 391, 96-116, 2020 | 60 | 2020 |
| Matrix-based set approximations and reductions in covering decision information systems A Tan, J Li, Y Lin, G Lin International Journal of Approximate Reasoning 59, 68-80, 2015 | 57 | 2015 |
| Relations of reduction between covering generalized rough sets and concept lattices J Chen, J Li, Y Lin, G Lin, Z Ma Information sciences 304, 16-27, 2015 | 55 | 2015 |
| Feature selection for multi-label learning based on kernelized fuzzy rough sets Y Li, Y Lin, J Liu, W Weng, Z Shi, S Wu Neurocomputing 318, 271-286, 2018 | 54 | 2018 |
| Online multi-label group feature selection J Liu, Y Lin, S Wu, C Wang Knowledge-Based Systems 143, 42-57, 2018 | 54 | 2018 |
