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Wei He 0017
Person information
- affiliation: Guangxi Normal University, Guilin, China
Other persons with the same name
- Wei He (aka: He Wei) — disambiguation page
- Wei He 0001
— University of Science and Technology Beijing, School of Automation and Electrical Engineering, China (and 2 more)
- Wei He 0002
- Wei He 0003
- Wei He 0004
- Wei He 0005
- Wei He 0006
- Wei He 0007
- Wei He 0008
- Wei He 0009
- Wei He 0010 — Huaihua College, College of Music and Dancing, China (and 2 more)
- Wei He 0011
- Wei He 0012 — University of Maryland, College Park, MD, USA
- Wei He 0013
- Wei He 0014 — Baidu Inc., Beijing, China (and 1 more)
- Wei He 0015
- Wei He 0016 — Changchun University of Science and Technology, China
- Wei (Joy) He (aka: Wei He 0018) — Texas Tech University, Rawls College of Business, Lubbock, TX, USA (and 2 more)
- Wei He 0019
- Wei He 0020
- Wei He 0021
- Wei He 0022
- Wei He 0023
- Wei He 0024 — Fudan University, School of Computer Science, Fudan NLP Group, Shanghai, China
- Wei He 0025
- Wei He 0026
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2010 – 2019
- 2019
- [j10]Xiaofeng Zhu
One-Step Multi-View Spectral Clustering. IEEE Trans. Knowl. Data Eng. 31(10): 2022-2034 (2019) - 2017
- [j9]Rongyao Hu, Xiaofeng Zhu
Graph self-representation method for unsupervised feature selection. Neurocomputing 220: 130-137 (2017) - [j8]Wei He, Xiaofeng Zhu
Unsupervised feature selection for visual classification via feature-representation property. Neurocomputing 236: 5-13 (2017) - [j7]Xiaohui Cheng, Yonghua Zhu, Jingkuan Song, Guoqiu Wen, Wei He:
A novel low-rank hypergraph feature selection for multi-view classification. Neurocomputing 253: 115-121 (2017) - [j6]Wei He, Xiaohui Cheng, Rongyao Hu, Yonghua Zhu, Guoqiu Wen:
Feature self-representation based hypergraph unsupervised feature selection via low-rank representation. Neurocomputing 253: 127-134 (2017) - [j5]Rongyao Hu, Jie Cao
Self-representation dimensionality reduction for multi-model classification. Neurocomputing 253: 154-161 (2017) - [j4]Wei He, Xiaofeng Zhu
Low-rank unsupervised graph feature selection via feature self-representation. Multim. Tools Appl. 76(9): 12149-12164 (2017) - [j3]Rongyao Hu, Debo Cheng
Low-rank feature selection for multi-view regression. Multim. Tools Appl. 76(16): 17479-17495 (2017) - [j2]Yonghua Zhu, Xuejun Zhang, Guoqiu Wen, Wei He, Debo Cheng
Double sparse-representation feature selection algorithm for classification. Multim. Tools Appl. 76(16): 17525-17539 (2017) - [j1]Yonggang Li
Spectral clustering based on hypergraph and self-re-presentation. Multim. Tools Appl. 76(16): 17559-17576 (2017) - [c4]Xiaofeng Zhu, Wei He, Yonggang Li
One-Step Spectral Clustering via Dynamically Learning Affinity Matrix and Subspace. AAAI 2017: 2963-2969 - [c3]Xiaofeng Zhu, Yonghua Zhu, Shichao Zhang, Rongyao Hu, Wei He:
Adaptive Hypergraph Learning for Unsupervised Feature Selection. IJCAI 2017: 3581-3587 - 2016
- [c2]Wei He, Xiaofeng Zhu
Unsupervised Hypergraph Feature Selection with Low-Rank and Self-Representation Constraints. ADMA 2016: 172-187 - [c1]Rongyao Hu, Xiaofeng Zhu
Supervised Feature Selection by Robust Sparse Reduced-Rank Regression. ADMA 2016: 700-713
Coauthor Index
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