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Regularized matrix regression

Citations

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Cited by:

  1. Pan Shang & Lingchen Kong, 2021. "Regularization Parameter Selection for the Low Rank Matrix Recovery," Journal of Optimization Theory and Applications, Springer, vol. 189(3), pages 772-792, June.
  2. Yang, Yaohong & Zhao, Weihua & Wang, Lei, 2023. "Online regularized matrix regression with streaming data," Computational Statistics & Data Analysis, Elsevier, vol. 187(C).
  3. Xiaoshan Li & Da Xu & Hua Zhou & Lexin Li, 2018. "Tucker Tensor Regression and Neuroimaging Analysis," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 10(3), pages 520-545, December.
  4. Yang, Yaohong & Wang, Lei & Liu, Jiamin & Li, Rui & Lian, Heng, 2023. "Communication-efficient estimation of quantile matrix regression for massive datasets," Computational Statistics & Data Analysis, Elsevier, vol. 187(C).
  5. Zhao, Junlong & Niu, Lu & Zhan, Shushi, 2017. "Trace regression model with simultaneously low rank and row(column) sparse parameter," Computational Statistics & Data Analysis, Elsevier, vol. 116(C), pages 1-18.
  6. Xu Gao & Weining Shen & Liwen Zhang & Jianhua Hu & Norbert J. Fortin & Ron D. Frostig & Hernando Ombao, 2021. "Regularized matrix data clustering and its application to image analysis," Biometrics, The International Biometric Society, vol. 77(3), pages 890-902, September.
  7. Wang, Lei & Zhang, Jing & Li, Bo & Liu, Xiaohui, 2022. "Quantile trace regression via nuclear norm regularization," Statistics & Probability Letters, Elsevier, vol. 182(C).
  8. Yiting Ma & Pan Shang & Lingchen Kong, 2025. "Tuning parameter selection for the adaptive nuclear norm regularized trace regression," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 77(3), pages 491-516, June.
  9. Xin Li & Dongya Wu, 2025. "Low-Rank Matrix Recovery Via Nonconvex Optimization Methods with Application to Errors-in-Variables Matrix Regression," Journal of Optimization Theory and Applications, Springer, vol. 205(3), pages 1-27, June.
  10. Wang, Dong & Liu, Xialu & Chen, Rong, 2019. "Factor models for matrix-valued high-dimensional time series," Journal of Econometrics, Elsevier, vol. 208(1), pages 231-248.
  11. Fijnanda van Klingeren & Vincent Buskens, 2024. "Graduated sanctioning, endogenous institutions and sustainable cooperation in common-pool resources: An experimental test," Rationality and Society, , vol. 36(2), pages 183-229, May.
  12. Wei Hu & Tianyu Pan & Dehan Kong & Weining Shen, 2021. "Nonparametric matrix response regression with application to brain imaging data analysis," Biometrics, The International Biometric Society, vol. 77(4), pages 1227-1240, December.
  13. Junchen Li, 2025. "Robust matrix factor analysis method with adaptive parameter adjustment using Cauchy weighting," Computational Statistics, Springer, vol. 40(3), pages 1597-1620, March.
  14. Amado Villarreal González & Saidi Magaly Flores Sánchez & Miguel A. Flores Segovia, 2016. "Patrones de co-localización espacial de la industria aeroespacial en México," Estudios Económicos, El Colegio de México, Centro de Estudios Económicos, vol. 31(1), pages 169-211.
  15. Yin Xia & Lexin Li, 2017. "Hypothesis testing of matrix graph model with application to brain connectivity analysis," Biometrics, The International Biometric Society, vol. 73(3), pages 780-791, September.
  16. Federico Ferraccioli & Giovanna Menardi, 2023. "Modal clustering of matrix-variate data," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 17(2), pages 323-345, June.
  17. Luo, Chongliang & Liang, Jian & Li, Gen & Wang, Fei & Zhang, Changshui & Dey, Dipak K. & Chen, Kun, 2018. "Leveraging mixed and incomplete outcomes via reduced-rank modeling," Journal of Multivariate Analysis, Elsevier, vol. 167(C), pages 378-394.
  18. Zengchao Xu & Shan Luo & Zehua Chen, 2023. "A Portmanteau Local Feature Discrimination Approach to the Classification with High-dimensional Matrix-variate Data," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 85(1), pages 441-467, February.
  19. Canu, Stéphane & Fourdrinier, Dominique, 2017. "Unbiased risk estimates for matrix estimation in the elliptical case," Journal of Multivariate Analysis, Elsevier, vol. 158(C), pages 60-72.
  20. Niu, Lu & Liu, Xiumin & Zhao, Junlong, 2020. "Robust estimator of the correlation matrix with sparse Kronecker structure for a high-dimensional matrix-variate," Journal of Multivariate Analysis, Elsevier, vol. 177(C).
  21. Li, Mei & Kong, Lingchen, 2019. "Double fused Lasso penalized LAD for matrix regression," Applied Mathematics and Computation, Elsevier, vol. 357(C), pages 119-138.
  22. Hung Hung & Su‐Yun Huang, 2019. "Sufficient dimension reduction via random‐partitions for the large‐p‐small‐n problem," Biometrics, The International Biometric Society, vol. 75(1), pages 245-255, March.
  23. Xiumin Liu & Lu Niu & Junlong Zhao, 2023. "Statistical inference on the significance of rows and columns for matrix-valued data in an additive model," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 32(3), pages 785-828, September.
  24. Philip T. Reiss & Jeff Goldsmith & Han Lin Shang & R. Todd Ogden, 2017. "Methods for Scalar-on-Function Regression," International Statistical Review, International Statistical Institute, vol. 85(2), pages 228-249, August.
  25. Xin Li & Dongya Wu, 2024. "Low-rank matrix estimation via nonconvex optimization methods in multi-response errors-in-variables regression," Journal of Global Optimization, Springer, vol. 88(1), pages 79-114, January.
  26. Li, Xin & Wu, Dongya, 2025. "Low-rank matrix estimation via nonconvex spectral regularized methods in errors-in-variables matrix regression," European Journal of Operational Research, Elsevier, vol. 323(2), pages 626-641.
  27. Ruonan Li & Luo Xiao, 2023. "Latent factor model for multivariate functional data," Biometrics, The International Biometric Society, vol. 79(4), pages 3307-3318, December.
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