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Journal of Computational and Graphical Statistics Volume 28, 2019 - Issue 1
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Optimization with Penalization

A Penalized Likelihood Method for Classification With Matrix-Valued Predictors

Aaron J. MolstadBiostatistics Program, Fred Hutchinson Cancer Research Center, Seattle, WAView further author information
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Adam J. RothmanSchool of Statistics, University of Minnesota, Minneapolis, MNView further author information
Pages 11-22 | Received 01 Sep 2016, Published online: 20 Aug 2018

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Geoffrey Z. Thompson, Ranjan Maitra, William Q. Meeker & Ashraf F. Bastawros. (2020) Classification With the Matrix-Variate-t Distribution. Journal of Computational and Graphical Statistics 29:3, pages 668-674.
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Keqian Min, Qing Mai & Junge Li. (2023) Optimality in high-dimensional tensor discriminant analysis. Pattern Recognition 143, pages 109803.
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Xin Chen, Dan Yang, Yan Xu, Yin Xia, Dong Wang & Haipeng Shen. (2023) Testing and support recovery of correlation structures for matrix-valued observations with an application to stock market data. Journal of Econometrics 232:2, pages 544-564.
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Zengchao Xu, Shan Luo & Zehua Chen. (2021) A Portmanteau Local Feature Discrimination Approach to the Classification with High-dimensional Matrix-variate Data. Sankhya A 85:1, pages 441-467.
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Hao Chen, Ying Guo, Yong He, Jiadong Ji, Lei Liu, Yufeng Shi, Yikai Wang, Long Yu & Xinsheng Zhang. (2022) Simultaneous differential network analysis and classification for matrix-variate data with application to brain connectivity. Biostatistics 23:3, pages 967-989.
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Yu Wang, Zeyu Sun, Dogyoon Song & Alfred Hero. (2022) Kronecker-structured covariance models for multiway data. Statistics Surveys 16:none.
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