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| 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 | 140 | 2018 |
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| An effective collaborative filtering algorithm based on user preference clustering J Zhang, Y Lin, M Lin, J Liu Applied Intelligence 45, 230-240, 2016 | 121 | 2016 |
| 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 | 98 | 2018 |
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| 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 | 97 | 2018 |
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| A graph approach for fuzzy-rough feature selection J Chen, J Mi, Y Lin Fuzzy Sets and Systems 391, 96-116, 2020 | 66 | 2020 |
| 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 | 61 | 2018 |
| 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 | 59 | 2015 |
| 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 | 58 | 2015 |
| Online multi-label group feature selection J Liu, Y Lin, S Wu, C Wang Knowledge-Based Systems 143, 42-57, 2018 | 57 | 2018 |
