| A new formulation of linear discriminant analysis for robust dimensionality reduction H Zhao, Z Wang, F Nie IEEE Transactions on Knowledge and Data Engineering 31 (4), 629-640, 2018 | 112 | 2018 |
| Towards Robust Discriminative Projections Learning via Non-Greedy -Norm MinMax F Nie, Z Wang, R Wang, Z Wang, X Li IEEE transactions on pattern analysis and machine intelligence 43 (6), 2086-2100, 2019 | 86 | 2019 |
| Discriminative Feature Selection via A Structured Sparse Subspace Learning Module Z Wang, F Nie, L Tian, R Wang, X Li IJCAI 2020, 2020 | 81 | 2020 |
| Subspace Sparse Discriminative Feature Selection F Nie, Z Wang, L Tian, R Wang, X Li IEEE Transactions on Cybernetics, 2020 | 72 | 2020 |
| Adaptive local linear discriminant analysis F Nie, Z Wang, R Wang, Z Wang, X Li ACM Transactions on Knowledge Discovery from Data (TKDD) 14 (1), 1-19, 2020 | 67 | 2020 |
| Submanifold-preserving discriminant analysis with an auto-optimized graph F Nie, Z Wang, R Wang, X Li IEEE Transactions on Cybernetics, 2019 | 65 | 2019 |
| Orthogonal least squares regression for feature extraction H Zhao, Z Wang, F Nie Neurocomputing 216, 200-207, 2016 | 51 | 2016 |
| Curriculum audiovisual learning D Hu, Z Wang, H Xiong, D Wang, F Nie, D Dou arXiv preprint arXiv:2001.09414, 2020 | 46 | 2020 |
| Adaptive local embedding learning for semi-supervised dimensionality reduction F Nie, Z Wang, R Wang, X Li IEEE Transactions on Knowledge and Data Engineering 34 (10), 4609-4621, 2021 | 44 | 2021 |
| Local structured feature learning with dynamic maximum entropy graph Z Wang, F Nie, R Wang, H Yang, X Li Pattern Recognition 111, 107673, 2020 | 34 | 2020 |
| Joint anchor graph embedding and discrete feature scoring for unsupervised feature selection Z Wang, D Wu, R Wang, F Nie, F Wang IEEE Transactions on Neural Networks and Learning Systems, 2022 | 26 | 2022 |
| Sparse trace ratio LDA for supervised feature selection Z Li, F Nie, D Wu, Z Wang, X Li IEEE transactions on cybernetics 54 (4), 2420-2433, 2023 | 25 | 2023 |
| Sparse and flexible projections for unsupervised feature selection R Wang, C Zhang, J Bian, Z Wang, F Nie, X Li IEEE Transactions on Knowledge and Data Engineering 35 (6), 6362-6375, 2022 | 23 | 2022 |
| Geometric-inspired graph-based incomplete multi-view clustering Z Yang, H Zhang, Y Wei, Z Wang, F Nie, D Hu Pattern Recognition 147, 110082, 2024 | 20 | 2024 |
| Worst-case discriminative feature learning via max-min ratio analysis Z Wang, F Nie, C Zhang, R Wang, X Li IEEE Transactions on Pattern Analysis and Machine Intelligence 46 (1), 641-658, 2023 | 19 | 2023 |
| Fast spectral clustering with self-adapted bipartite graph learning X Yang, M Zhu, Y Cai, Z Wang, F Nie Information Sciences 644, 118810, 2023 | 19 | 2023 |
| Capped -Norm LDA for Outliers Robust Dimension Reduction Z Wang, F Nie, C Zhang, R Wang, X Li IEEE Signal Processing Letters 27, 1315-1319, 2020 | 18 | 2020 |
| Joint adaptive graph learning and discriminative analysis for unsupervised feature selection H Zhao, Q Li, Z Wang, F Nie Cognitive Computation 14 (3), 1211-1221, 2022 | 17 | 2022 |
| Fuzzy C-multiple-means clustering for hyperspectral image X Yang, M Zhu, B Sun, Z Wang, F Nie IEEE Geoscience and Remote Sensing Letters 20, 1-5, 2023 | 16 | 2023 |
| Multiclass Classification and Feature Selection Based on Least Squares Regression with Large Margin ZW Haifeng Zhao, Siqi Wang Neural computation 30 (10), 2781-2804, 2018 | 13 | 2018 |
Feiping NieOPTIMALE-mailová adresa ověřena na: mails.tsinghua.edu.cn