CONVERGENCE ANALYSIS OF PROXIMAL GRADIENT ALGORITHM WITH EXTRAPOLATION FOR A CLASS OF CONVEX NONSMOOTH MINIMIZATION PROBLEMS

被引:0
|
作者
Pan, Mengxi [1 ]
Wen, Bo [2 ]
机构
[1] Hebei Univ Technol, Sch Sci, Tianjin, Peoples R China
[2] Hebei Univ Technol, Inst Math, Tianjin, Peoples R China
来源
PACIFIC JOURNAL OF OPTIMIZATION | 2023年 / 19卷 / 03期
关键词
nonsmooth convex minimization; proximal gradient algorithm; extrapolation; convergence analysis;
D O I
暂无
中图分类号
C93 [管理学]; O22 [运筹学];
学科分类号
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要
In this paper, we consider the proximal gradient algorithm with extrapolation (PG(e)) for solving a class of nonsmooth convex minimization problems, whose objective function in the sum of a continuously differentiable convex function with Lipschitz gradient and a proper closed convex function. We first establish the subsequential convergence of iterate generated by PG(e), then we prove that the convergence rate of objective function is O (1/k), which implies that the convergence rate of FISTA with fixed restart is also O (1/k). Finally , we conduct some numerical experiments to illustrate the theoretical results
引用
收藏
页码:477 / 487
页数:11
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