Subspace learning-based graph regularized feature selection

Knowledge-Based Systems ◽

10.1016/j.knosys.2016.09.006 ◽

2016 ◽

Vol 112 ◽

pp. 152-165 ◽

Author(s):

Ronghua Shang ◽

Wenbing Wang ◽

Rustam Stolkin ◽

Licheng Jiao

Keyword(s):

Feature Selection ◽

Subspace Learning

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Joint Subspace Learning and Sparse Regression for Feature Selection in Kernel Space

Applications and Techniques in Information Security - Communications in Computer and Information Science ◽

10.1007/978-981-13-2907-4_13 ◽

2018 ◽

pp. 147-158 ◽

Author(s):

Long Chen ◽

Zhi Zhong

Keyword(s):

Feature Selection ◽

Subspace Learning ◽

Kernel Space ◽

Sparse Regression

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Maximum Correntropy Criterion-Based Sparse Subspace Learning for Unsupervised Feature Selection

IEEE Transactions on Circuits and Systems for Video Technology ◽

10.1109/tcsvt.2017.2783364 ◽

2019 ◽

Vol 29 (2) ◽

pp. 404-417 ◽

Author(s):

Nan Zhou ◽

Yangyang Xu ◽

Hong Cheng ◽

Zejian Yuan ◽

Badong Chen

Keyword(s):

Feature Selection ◽

Subspace Learning ◽

Unsupervised Feature Selection ◽

Maximum Correntropy Criterion

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Trace Ratio Criterion Based Large Margin Subspace Learning for Feature Selection

IEEE Access ◽

10.1109/access.2018.2888924 ◽

2019 ◽

Vol 7 ◽

pp. 6461-6472 ◽

Author(s):

Hui Luo ◽

Jiqing Han

Keyword(s):

Feature Selection ◽

Subspace Learning ◽

Large Margin ◽

Ratio Criterion ◽

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Integrating joint feature selection into subspace learning: A formulation of 2DPCA for outliers robust feature selection

Neural Networks ◽

10.1016/j.neunet.2019.08.030 ◽

2020 ◽

Vol 121 ◽

pp. 441-451 ◽

Author(s):

Imran Razzak ◽

Raghib Abu Saris ◽

Michael Blumenstein ◽

Guandong Xu

Keyword(s):

Feature Selection ◽

Subspace Learning

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Subspace learning for unsupervised feature selection via matrix factorization

Pattern Recognition ◽

10.1016/j.patcog.2014.08.004 ◽

2015 ◽

Vol 48 (1) ◽

pp. 10-19 ◽

Author(s):

Shiping Wang ◽

Witold Pedrycz ◽

Qingxin Zhu ◽

William Zhu

Keyword(s):

Feature Selection ◽

Matrix Factorization ◽

Subspace Learning ◽

Unsupervised Feature Selection

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Subspace learning for unsupervised feature selection via adaptive structure learning and rank approximation

Neurocomputing ◽

10.1016/j.neucom.2020.06.111 ◽

2020 ◽

Vol 413 ◽

pp. 72-84

Author(s):

Ronghua Shang ◽

Kaiming Xu ◽

Licheng Jiao

Keyword(s):

Feature Selection ◽

Structure Learning ◽

Subspace Learning ◽

Unsupervised Feature Selection ◽

Adaptive Structure ◽

Rank Approximation

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Discriminative sparse subspace learning and its application to unsupervised feature selection

ISA Transactions ◽

10.1016/j.isatra.2015.12.011 ◽

2016 ◽

Vol 61 ◽

pp. 104-118 ◽

Author(s):

Nan Zhou ◽

Hong Cheng ◽

Witold Pedrycz ◽

Yong Zhang ◽

Huaping Liu

Keyword(s):

Feature Selection ◽

Subspace Learning ◽

Unsupervised Feature Selection

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Feature Selection Based Transfer Subspace Learning for Speech Emotion Recognition

IEEE Transactions on Affective Computing ◽

10.1109/taffc.2018.2800046 ◽

2020 ◽

Vol 11 (3) ◽

pp. 373-382 ◽

Author(s):

Peng Song ◽

Wenming Zheng

Keyword(s):

Feature Selection ◽

Emotion Recognition ◽

Subspace Learning ◽

Speech Emotion Recognition

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Robust Sparse Subspace Learning for unsupervised feature selection

2016 International Joint Conference on Neural Networks (IJCNN) ◽

10.1109/ijcnn.2016.7727748 ◽

2016 ◽

Author(s):

Feng Wang ◽

Qi Rao ◽

Yongquan Zhang ◽

Xu Chen

Keyword(s):

Feature Selection ◽

Subspace Learning ◽

Unsupervised Feature Selection

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Joint self-representation and subspace learning for unsupervised feature selection

World Wide Web ◽

10.1007/s11280-017-0508-3 ◽

2017 ◽

Vol 21 (6) ◽

pp. 1745-1758 ◽

Author(s):

Ruili Wang ◽

Ming Zong

Keyword(s):

Feature Selection ◽

Subspace Learning ◽

Unsupervised Feature Selection

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