Proceedings of the 2025 4th International Conference on Mathematical Statistics and Economic Analysis (MSEA 2025)

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Optimal Subsampling Algorithms for Imbalanced Big Data Regression Problems

Authors
Fangnan Zheng1, *
1College of Foreign Languages and Cultures, Xiamen University, Xiamen, Fujian Province, 361005, China
*Corresponding author. Email: 12220212203526@stu.xmu.edu.cn
Corresponding Author
Fangnan Zheng
Available Online 20 February 2026.
DOI
10.2991/978-94-6463-992-6_22How to use a DOI?
Keywords
Subsampling; Linear Regression; Logistic Regression; Softmax Regression; Generalized Linear Models
Abstract

This review focuses on optimal subsampling methods tailored for linear regression, logistic regression, softmax regression, and generalized linear models. We discuss the principles behind these methods, emphasizing their effectiveness and efficiency. The review also points out the consistency and asymptotic normality of the estimators.

Copyright
© 2026 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2025 4th International Conference on Mathematical Statistics and Economic Analysis (MSEA 2025)
Series
Advances in Economics, Business and Management Research
Publication Date
20 February 2026
ISBN
978-94-6463-992-6
ISSN
2352-5428
DOI
10.2991/978-94-6463-992-6_22How to use a DOI?
Copyright
© 2026 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Fangnan Zheng
PY  - 2026
DA  - 2026/02/20
TI  - Optimal Subsampling Algorithms for Imbalanced Big Data Regression Problems
BT  - Proceedings of the 2025 4th International Conference on Mathematical Statistics and Economic Analysis (MSEA 2025)
PB  - Atlantis Press
SP  - 215
EP  - 229
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-992-6_22
DO  - 10.2991/978-94-6463-992-6_22
ID  - Zheng2026
ER  -