A majorization penalty method for SVM with sparse constraint-Reference-Cited by-同舟云学术

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A majorization penalty method for SVM with sparse constraint

Published:2023-01-09 Issue:3 Volume:38 Page:474-494
ISSN:1055-6788
Container-title:Optimization Methods and Software
language:en
Short-container-title:Optimization Methods and Software

Author:

Lu Sitong¹,Li Qingna²

Affiliation:

1. School of Mathematics and Statistics, Beijing Institute of Technology, Beijing, People's Republic of China

2. School of Mathematics and Statistics/Beijing Key Laboratory on MCAACI/Key Laboratory of Mathematical Theory and Computation in Information Security, Beijing Institute of Technology, Beijing, People's Republic of China

Funder

National Science Foundation of China

Publisher

Informa UK Limited

Subject

Applied Mathematics,Control and Optimization,Software

Link

https://www.tandfonline.com/doi/pdf/10.1080/10556788.2022.2142584

Reference34 articles.

1. A New Text Categorization Technique Using Distributional Clustering and Learning Logic

2. On the approximability of minimizing nonzero variables or unsatisfied relations in linear systems

3. Support Vector Regression

4. Support Vector Machines with the Ramp Loss and the Hard Margin Loss

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Optimality Conditions and Gradient Descent Newton Pursuit for 0/1-Loss and Sparsity Constrained Optimization;Asia-Pacific Journal of Operational Research;2023-11-18

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