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CPQR-based randomized algorithms for generalized CUR decompositions

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Abstract

Based on the column pivoted QR decomposition, we propose some randomized algorithms including pass-efficient ones for the generalized CUR decompositions of matrix pair and matrix triplet. Detailed error analyses of these algorithms are provided. Numerical experiments are given to test the proposed randomized algorithms.

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The data that support the findings of this study are available from the corresponding author upon reasonable request.

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Acknowledgements

The authors would like to thank the editor and the anonymous reviewers for their detailed comments and helpful sugesstions, which helped considerably to improve the quality of the paper.

Funding

The work is supported by the National Natural Science Foundation of China (Nos. 11671060, 12271108), the Natural Science Foundation of Chongqing, China (No. cstc2019jcyj-msxmX0267) and Shanghai Municipal Science and Technology Commission (no. 23WZ2501400).

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Authors and Affiliations

  1. College of Mathematics and Statistics, Chongqing University, Chongqing, 401331, People’s Republic of China

    Guihua Zhang & Hanyu Li

  2. School of Mathematical Sciences and Shanghai Key Laboratory of Contemporary Applied Mathematics, Fudan University, Shanghai, 200433, People’s Republic of China

    Yimin Wei

Authors
  1. Guihua Zhang
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  2. Hanyu Li
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  3. Yimin Wei
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All the authors contributed to the study conception and design, and read and approved the final manuscript.

Corresponding author

Correspondence to Hanyu Li.

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The authors declare that they have no conflict of interest.

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Communicated by Xiang Wang.

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The work is supported by the National Natural Science Foundation of China (Nos. 11671060, 12271108), the Natural Science Foundation of Chongqing, China (No. cstc2019jcyj-msxmX0267) and Shanghai Municipal Science and Technology Commission (no. 23WZ2501400).

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Cite this article

Zhang, G., Li, H. & Wei, Y. CPQR-based randomized algorithms for generalized CUR decompositions. Comp. Appl. Math. 43, 132 (2024). https://doi.org/10.1007/s40314-024-02642-5

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  • DOI: https://doi.org/10.1007/s40314-024-02642-5

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