An Inexact Accelerated Proximal Gradient Method and a Dual Newton-CG Method for the Maximal Entropy Problem

被引:7
|
作者
Wang, Chengjing [1 ,2 ]
Xu, Aimin [3 ]
机构
[1] Southwest Jiaotong Univ, Sch Math, Chengdu 610031, Peoples R China
[2] Southwest Jiaotong Univ, Inst Appl Math, Chengdu 610031, Peoples R China
[3] Zhejiang Wanli Univ, Inst Math, Ningbo 315100, Zhejiang, Peoples R China
基金
中国国家自然科学基金;
关键词
Maximal entropy problem; Inexact accelerated proximal gradient method; Newton-CG method; Semi-smoothness; IMAGE-RECONSTRUCTION; ALGORITHM; EQUATIONS;
D O I
10.1007/s10957-012-0150-2
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
This paper describes an algorithm to solve large-scale maximal entropy problems. The algorithm employs an inexact accelerated proximal gradient method to generate an initial iteration point which is important; then it applies the Newton-CG method to the dual problem. Numerical experiments illustrate that the algorithm can supply an acceptable and even highly accurate solution, while algorithms without generating a good initial point may probably fail.
引用
收藏
页码:436 / 450
页数:15
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