RELAXED INERTIAL PROJECTIVE FORWARD-BACKWARD SPLITTING ALGORITHMS FOR REGULARIZED LEAST SQUARE PROBLEMS

被引：0

作者：

Cholamjiak, Watcharaporn ^{[1
]}

Dutta, Hemen ^{[2
]}

机构：

[1] Univ Phayao, Sch Sci, Phayao 56000, Thailand

[2] Gauhati Univ, Dept Math, Gauhati 781014, India

来源：

COMPTES RENDUS DE L ACADEMIE BULGARE DES SCIENCES | 2024年 / 77卷 / 04期

关键词：

inertial technique; projective method; regularized least square problem; forward-backward splitting algorithm; variational inclusion problems; SIGNAL RECOVERY; OPTIMIZATION; LASSO;

D O I：

10.7546/CRABS.2024.04.03

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

This study presents flexible conditions of the inertial extrapolation parameter for easy implementation that is added to the algorithm in faster convergence. Modified inertial forward -backward splitting algorithms for solving variational inclusion problems are introduced to apply to solve the LASSO problem for image restoration and signal recovery, and the elastic net model for classification problem. Projection methods are used in the final step for narrowing down the search field, resulting in a better solution.

引用

页码：496 / 503

页数：8

共 18 条

[1] The Trimmed Lasso: Sparse Recovery Guarantees and Practical Optimization by the Generalized Soft-Min Penalty [J].