| Efficient tree classifiers for large scale datasets F Wang, Q Wang, F Nie, W Yu, R Wang Neurocomputing 284, 70-79, 2018 | 54 | 2018 |
| A linear multivariate binary decision tree classifier based on K-means splitting F Wang, Q Wang, F Nie, Z Li, W Yu, F Ren Pattern Recognition 107, 107521, 2020 | 52 | 2020 |
| Unsupervised linear discriminant analysis for jointly clustering and subspace learning F Wang, Q Wang, F Nie, Z Li, W Yu, R Wang IEEE Transactions on Knowledge and Data Engineering 33 (3), 1276 - 1290, 2021 | 38 | 2021 |
| A forest of trees with principal direction specified oblique split on random subspace F Wang, Q Wang, F Nie, W Yu, R Wang, Z Li Neurocomputing 379, 413-425, 2020 | 5 | 2020 |
| An Effective Clustering Optimization Method for Unsupervised Linear Discriminant Analysis Q Wang, F Wang, F Ren, Z Li, F Nie IEEE Transactions on Knowledge and Data Engineering 35 (4), 3444 - 3457, 2023 | 3 | 2023 |
| Clustering-based latent variable models for monocular non-rigid 3d shape recovery Q Wang, F Wang, D Li, X Wang International Conference on Intelligent Computing, 162-172, 2014 | 3 | 2014 |
| Efficient random subspace decision forests with a simple probability dimensionality setting scheme Q Wang, F Wang, Z Li, P Jiang, F Ren, F Nie Information Sciences, 118993, 2023 | 2 | 2023 |
