Skip to content
RDL
Network
Ekosistem
Uygulama değiştir
EN
Hakkımızda
SSS
Giriş yap
Başla
Local-Structure Adaptive Sparse Subspace Learning: An Iterative Approach to Unsupervised Feature Selection. — Nan Zhou (2015) | RDL Network
Back
Cite
Save
Save for later
Share
Home
Publications
Local-Structure Adaptive Sparse Subspace Learning: An Iterative Approach to Unsupervised Feature Selection.
Shared by
Witold Pedrycz
University of Alberta
Local-Structure Adaptive Sparse Subspace Learning: An Iterative Approach to Unsupervised Feature Selection.
Article
2015
en
Authors
+2 more
NZ
Nan Zhou
YX
Yangyang Xu
HC
Hong Cheng
Discussion
(0)
Sign in
to like and join the discussion.
No comments yet. Be the first to comment.
Related publications
Article
2015
Global and local structure preserving sparse subspace learning: An iterative approach to unsupervised feature selection
Nan Zhou
,
Yangyang Xu
,
Hong Cheng
,
Jun Fang
,
Witold Pedrycz
Preprint
2022
Global and Local Structure Preserving Sparse Subspace Learning: An Iterative Approach to Unsupervised Feature Selection
Nan Zhou
,
Yangyang Xu
,
Hong Cheng
,
Jun Fang
,
Witold Pedrycz
Article
2016
Discriminative sparse subspace learning and its application to unsupervised feature selection
Nan Zhou
,
Hong Cheng
,
Witold Pedrycz
,
Yong Zhang
,
Huaping Liu
Article
2016
Unsupervised feature selection by nonnegative sparsity adaptive subspace learning
Nan Zhou
,
Hong Cheng
,
Yali Zheng
,
Liangtian He
,
Witold Pedrycz
Article
2014
Subspace learning for unsupervised feature selection via matrix factorization
Shiping Wang
,
Witold Pedrycz
,
Qingxin Zhu
,
William Zhu
Discussion(0)
No comments yet. Be the first to comment.