BOOK-CHAPTER

Graph-regularized feature selection based on spectral learning and subspace learning

Keywords:
Feature selection Subspace topology Feature learning Artificial intelligence Exploit Pattern recognition (psychology) Graph Graph embedding Computer science Embedding Feature (linguistics) Minimum redundancy feature selection Dimensionality reduction Feature vector Machine learning Theoretical computer science

Metrics

3
Cited By
0.37
FWCI (Field Weighted Citation Impact)
30
Refs
0.68
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Face and Expression Recognition
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Advanced Computing and Algorithms
Social Sciences →  Social Sciences →  Urban Studies
Gene expression and cancer classification
Life Sciences →  Biochemistry, Genetics and Molecular Biology →  Molecular Biology

Related Documents

JOURNAL ARTICLE

Subspace learning-based graph regularized feature selection

Ronghua ShangWenbing WangRustam StolkinLicheng Jiao

Journal:   Knowledge-Based Systems Year: 2016 Vol: 112 Pages: 152-165
JOURNAL ARTICLE

Dual-graph regularized subspace learning based feature selection

Chao ShengPeng SongWeijian ZhangDongliang Chen

Journal:   Digital Signal Processing Year: 2021 Vol: 117 Pages: 103175-103175
JOURNAL ARTICLE

Dynamic subspace dual-graph regularized multi-label feature selection

Juncheng HuYonghao LiGaochao XuWanfu Gao

Journal:   Neurocomputing Year: 2021 Vol: 467 Pages: 184-196
© 2026 ScienceGate Book Chapters — All rights reserved.