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Multilinear Sparse Principal Component Analysis

IEEE Transactions on Neural Networks and Learning Systems, 2014
In this brief, multilinear sparse principal component analysis (MSPCA) is proposed for feature extraction from the tensor data. MSPCA can be viewed as a further extension of the classical principal component analysis (PCA), sparse PCA (SPCA) and the ...
Qingcai Chen, Zhihui Lai, David Zhang
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Eigenvectors from Eigenvalues Sparse Principal Component Analysis

Journal of Computational and Graphical Statistics, 2022
Hildreth Robert Frost
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Sparse multivariate functional principal component analysis

Stat, 2022
Jun Song, Kyongwon Kim
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Sparse principal component analysis using bootstrap method

Chemical Engineering Science, 2021
Salim Ahmed, Syed Imtiaz, Abdalhamid Rahoma   +2 more
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Sparse principal component analysis for high-dimensional stationary time series

Scandinavian Journal of Statistics, 2023
Masanobu Taniguchi, Yan Liu, Yuichi Gotō   +2 more
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An Alternating Manifold Proximal Gradient Method for Sparse Principal Component Analysis and Sparse Canonical Correlation Analysis

INFORMS Journal on Optimization, 2020
Shixiang Chen, Lingzhou Xue, Shiqian Ma
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“Tfm”: Sparse Online Principal Component for Tfm

Beibei Wu, Guangbao Guo
openaire   +1 more source

Novel variation mode decomposition integrated adaptive sparse principal component analysis and it application in fault diagnosis

ISA Transactions, 2022
Zhiqiang Geng, Yongming Han
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Sparse Principal Component Analysis via Variable Projection

SIAM Journal on Applied Mathematics, 2020
Krithika Manohar, Aleksandr Aravkin, Jose Nathan Kutz   +2 more
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A Selective Overview of Sparse Principal Component Analysis

Proceedings of the IEEE, 2018
Lingzhou Xue, Hui Zou
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