Machine learning model based on non-convex penalized huberized-SVM
Article Properties
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LanguageEnglish
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DOI (url)
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Publication Date2024/03/01
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Indian UGC (journal)
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Refrences22
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Peng Wang
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Ji Guo
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Lin-Feng Li
Cite
Wang, Peng, et al. “Machine Learning Model Based on Non-Convex Penalized Huberized-SVM”. Journal of Electronic Science and Technology, vol. 22, no. 1, 2024, p. 100246, https://doi.org/10.1016/j.jnlest.2024.100246.
Wang, P., Guo, J., & Li, L.-F. (2024). Machine learning model based on non-convex penalized huberized-SVM. Journal of Electronic Science and Technology, 22(1), 100246. https://doi.org/10.1016/j.jnlest.2024.100246
Wang, Peng, Ji Guo, and Lin-Feng Li. “Machine Learning Model Based on Non-Convex Penalized Huberized-SVM”. Journal of Electronic Science and Technology 22, no. 1 (2024): 100246. https://doi.org/10.1016/j.jnlest.2024.100246.
Wang P, Guo J, Li LF. Machine learning model based on non-convex penalized huberized-SVM. Journal of Electronic Science and Technology. 2024;22(1):100246.
Journal Categories
Science
Mathematics
Instruments and machines
Electronic computers
Computer science
Technology
Electrical engineering
Electronics
Nuclear engineering
Refrences
| Title | Journal | Journal Categories | Citations | Publication Date |
|---|---|---|---|---|
| On LASSO for predictive regression | Journal of Econometrics |
| 21 | 2022 |
| Structured sparse support vector machine with ordered features | Journal of Applied Statistics |
| 1 | 2022 |
The Higher-Order of Adaptive Lasso and Elastic Net Methods for Classification on High Dimensional Data | Mathematics |
| 14 | 2021 |
Variable Selection for Support Vector Machines in Moderately High Dimensions | Journal of the Royal Statistical Society Series B: Statistical Methodology |
| 36 | 2016 |
| A fast unified algorithm for solving group-lasso penalize learning problems | Statistics and Computing |
| 124 | 2015 |
Refrences Analysis
The category
Science: Mathematics 5
is the most frequently represented among the references in this article. It primarily includes studies from Annals of Operations Research and Advances in Computational Mathematics. The chart below illustrates the number of referenced publications per year.