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 计算数学 2018, Vol. 40 Issue (4): 367-386    DOI:
 论文 最新目录 | 下期目录 | 过刊浏览 | 高级检索 Previous Articles  |  Next Articles A SELF-ADAPTIVE GENERALIZED ALTERNATING DIRECTION METHOD OF MULTIPLIERS
Jiang Fan, Liu Yamei, Cai Xingju
School of Mathematical Sciences, Nanjing Normal University, Nanjing 210023, China
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Abstract： Generalized alternating direction method of multipliers (G-ADMM) is effective in solving the convex optimization problem. When the subproblem is difficult to solve in practical problem, we can add the proximal term in the subproblem. The positive definiteness of the proximal matrix guarantees the convergence while resulting in the tiny step size. A new study indicates that the proximal matrix can be indefinite. In this paper, based on the frame of G-ADMM with indefinite proximal term, we propose a self-adaptive G-ADMM while the proximal matrix is dynamically selected to increase the step size. Under mild assumptions, we prove the global convergence of the proposed method. The preliminary numerical results indicate that the new algorithm is efficient.

 引用本文: . 一类自适应广义交替方向乘子法[J]. 计算数学, 2018, 40(4): 367-386. . A SELF-ADAPTIVE GENERALIZED ALTERNATING DIRECTION METHOD OF MULTIPLIERS[J]. Mathematica Numerica Sinica, 2018, 40(4): 367-386.

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