| Multi-label feature selection based on max-dependency and min-redundancy Y Lin, Q Hu, J Liu, J Duan Neurocomputing 168, 92-103, 2015 | 242 | 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 | 170 | 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 | 162 | 2016 |
| 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 | 132 | 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 | 119 | 2016 |
| Feature selection based on quality of information J Liu, Y Lin, M Lin, S Wu, J Zhang Neurocomputing 225, 11-22, 2017 | 85 | 2017 |
| 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 | 58 | 2018 |
| Online multi-label group feature selection J Liu, Y Lin, S Wu, C Wang Knowledge-Based Systems 143, 42-57, 2018 | 56 | 2018 |
| Multi-label feature selection based on label correlations and feature redundancy Y Fan, B Chen, W Huang, J Liu, W Weng, W Lan Knowledge-Based Systems 241, 108256, 2022 | 48 | 2022 |
| Manifold learning with structured subspace for multi-label feature selection Y Fan, J Liu, P Liu, Y Du, W Lan, S Wu Pattern Recognition 120, 108169, 2021 | 45 | 2021 |
| Different classes’ ratio fuzzy rough set based robust feature selection Y Li, S Wu, Y Lin, J Liu Knowledge-Based Systems 120, 74-86, 2017 | 45 | 2017 |
| Feature selection for multi-label learning with streaming label J Liu, Y Li, W Weng, J Zhang, B Chen, S Wu Neurocomputing 387, 268-278, 2020 | 43 | 2020 |
| Group-preserving label-specific feature selection for multi-label learning J Zhang, H Wu, M Jiang, J Liu, S Li, Y Tang, J Long Expert Systems with Applications 213, 118861, 2023 | 35 | 2023 |
| MULFE: multi-label learning via label-specific feature space ensemble Y Lin, Q Hu, J Liu, X Zhu, X Wu ACM Transactions on Knowledge Discovery from Data (TKDD) 16 (1), 1-24, 2021 | 35 | 2021 |
| Non-sparse label specific features selection for multi-label classification W Weng, YN Chen, CL Chen, SX Wu, JH Liu Neurocomputing 377, 85-94, 2020 | 30 | 2020 |
| Feature selection for multi-label learning with missing labels C Wang, Y Lin, J Liu Applied Intelligence 49, 3027-3042, 2019 | 28 | 2019 |
| Multi-label feature selection with local discriminant model and label correlations Y Fan, J Liu, W Weng, B Chen, Y Chen, S Wu Neurocomputing 442, 98-115, 2021 | 27 | 2021 |
| A variable precision grey-based multi-granulation rough set model and attribute reduction Y Kang, S Wu, Y Li, J Liu, B Chen Knowledge-Based Systems 148, 131-145, 2018 | 27 | 2018 |
| Multi-label feature selection with constraint regression and adaptive spectral graph Y Fan, J Liu, W Weng, B Chen, Y Chen, S Wu Knowledge-Based Systems 212, 106621, 2021 | 26 | 2021 |
| Fuzzy mutual information-based multilabel feature selection with label dependency and streaming labels J Liu, Y Lin, W Ding, H Zhang, J Du IEEE Transactions on Fuzzy Systems 31 (1), 77-91, 2022 | 25 | 2022 |
Yaojin LinMinnan Normal University在 mnnu.edu.cn 的电子邮件经过验证
