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UNSUPERVISED FEATURE SELECTION BY MANIFOLD REGULARIZED SELF-REPRESENTATION

Abstract: 

Unsupervised feature selection has been proven to be an efficient technique in mitigating the curse of dimensionality. It helps to understand and analyze the prevalent high-dimensional unlabeled data. Recently, based on the self-similarity property of objects, self-representation which assumes that a feature can be represented by the linear combination of its relevant features has been successfully used in unsupervised feature selection. In this paper, we propose a novel algorithm termed Manifold Regularized Selfrepresentation(MRSR) based on the self-representation ability of features. The L2;1-norm constraint is imposed on representation coefficient matrix to select the most discriminant features and remove the irrelevant ones simultaneously. We further incorporate the effective manifold regularization term into MRSR to ensure that features can be represented at utmost with minimum representation residual. Extensive experimental results on several benchmark datasets validate the effectiveness of our method.

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Paper Details

Authors:
Siqi Liang, Pengfei Zhu, Qinghua Hu, Chongqing Zhang
Submitted On:
13 September 2017 - 12:13am
Short Link:
Type:
Poster
Event:
Presenter's Name:
Qian Xu
Paper Code:
1266
Document Year:
2017
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Document Files

MRSR_ICIP_1266

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[1] Siqi Liang, Pengfei Zhu, Qinghua Hu, Chongqing Zhang, "UNSUPERVISED FEATURE SELECTION BY MANIFOLD REGULARIZED SELF-REPRESENTATION", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1958. Accessed: Nov. 23, 2017.
@article{1958-17,
url = {http://sigport.org/1958},
author = {Siqi Liang; Pengfei Zhu; Qinghua Hu; Chongqing Zhang },
publisher = {IEEE SigPort},
title = {UNSUPERVISED FEATURE SELECTION BY MANIFOLD REGULARIZED SELF-REPRESENTATION},
year = {2017} }
TY - EJOUR
T1 - UNSUPERVISED FEATURE SELECTION BY MANIFOLD REGULARIZED SELF-REPRESENTATION
AU - Siqi Liang; Pengfei Zhu; Qinghua Hu; Chongqing Zhang
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1958
ER -
Siqi Liang, Pengfei Zhu, Qinghua Hu, Chongqing Zhang. (2017). UNSUPERVISED FEATURE SELECTION BY MANIFOLD REGULARIZED SELF-REPRESENTATION. IEEE SigPort. http://sigport.org/1958
Siqi Liang, Pengfei Zhu, Qinghua Hu, Chongqing Zhang, 2017. UNSUPERVISED FEATURE SELECTION BY MANIFOLD REGULARIZED SELF-REPRESENTATION. Available at: http://sigport.org/1958.
Siqi Liang, Pengfei Zhu, Qinghua Hu, Chongqing Zhang. (2017). "UNSUPERVISED FEATURE SELECTION BY MANIFOLD REGULARIZED SELF-REPRESENTATION." Web.
1. Siqi Liang, Pengfei Zhu, Qinghua Hu, Chongqing Zhang. UNSUPERVISED FEATURE SELECTION BY MANIFOLD REGULARIZED SELF-REPRESENTATION [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1958