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Zhu, W., Song, Y. and Xiao, Y. (2022) Robust Support Vector Machine Classifier with Truncated Loss Function by Gradient Algorithm. Computers & Industrial Engineering, 172, Article 108630.

has been cited by the following article:

• TITLE: The Modified BAPGs Method for Support Vector Machine Classifier with Truncated Loss

  AUTHORS: Kexin Ren

  KEYWORDS: HTPSVM, Bregman Distance, BAPGs Algorithm

  JOURNAL NAME: Applied Mathematics, Vol.15 No.4, April 10, 2024

  ABSTRACT: In this paper, we modify the Bregman APGs (BAPGs) method proposed in (Wang, L, et al.) for solving the support vector machine problem with truncated loss (HTPSVM) given in (Zhu, W, et al.), we also add an adaptive parameter selection technique based on (Ren, K, et al.). In each iteration, we use the linear approximation method to get the explicit solution of the subproblem and set a function to apply the Bregman distance. Finally, numerical experiments are performed to verify the efficiency of BAPGs.