Top-k discriminative feature selection with uncorrelated and ℓ2,0-norm equation constraints
-
Published:2024-09
Issue:
Volume:598
Page:128069
-
ISSN:0925-2312
-
Container-title:Neurocomputing
-
language:en
-
Short-container-title:Neurocomputing
Author:
Wang Jingyu,
Ma ZhenyuORCID,
Nie Feiping,
Li Xuelong
Reference50 articles.
1. Z. Kang, C. Peng, Q. Cheng, Robust PCA Via Nonconvex Rank Approximation, in: 2015 IEEE International Conference on Data Mining, 2015, pp. 211–220.
2. X. Li, M. Chen, F. Nie, Q. Wang, Locality Adaptive Discriminant Analysis, in: Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017, pp. 2201–2207.
3. Unsupervised feature selection via adaptive hypergraph regularized latent representation learning;Ding;Neurocomputing,2020
4. Unsupervised feature selection via discrete spectral clustering and feature weights;Shang;Neurocomputing,2023
5. Self-paced principal component analysis;Kang;Pattern Recognit.,2023