An Inertial Forward-Backward Algorithm for Monotone Inclusions

被引:334
|
作者
Lorenz, Dirk A. [1 ]
Pock, Thomas [2 ,3 ]
机构
[1] TU Braunschweig, Inst Anal & Algebra, D-38092 Braunschweig, Germany
[2] Graz Univ Technol, Inst Comp Graph & Vis, A-8010 Graz, Austria
[3] AIT Austrian Inst Technol GmbH, Safety & Secur Dept, A-1220 Vienna, Austria
基金
奥地利科学基金会;
关键词
Convex optimization; Forward-backward splitting; Monotone inclusions; Primal-dual algorithms; Saddle-point problems; Image restoration; PRIMAL-DUAL ALGORITHMS; THRESHOLDING ALGORITHM; SPLITTING ALGORITHM; WEAK-CONVERGENCE; PROXIMAL METHOD; OPERATORS; OPTIMIZATION; SUM;
D O I
10.1007/s10851-014-0523-2
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, we propose an inertial forward-backward splitting algorithm to compute a zero of the sum of two monotone operators, with one of the two operators being co-coercive. The algorithm is inspired by the accelerated gradient method of Nesterov, but can be applied to a much larger class of problems including convex-concave saddle point problems and general monotone inclusions. We prove convergence of the algorithm in a Hilbert space setting and show that several recently proposed first-order methods can be obtained as special cases of the general algorithm. Numerical results show that the proposed algorithm converges faster than existing methods, while keeping the computational cost of each iteration basically unchanged.
引用
收藏
页码:311 / 325
页数:15
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