R-linear convergence of the Barzilai and Borwein gradient method

被引:227
作者
Dai, YH
Liao, LZ
机构
[1] Chinese Acad Sci, Acad Math & Syst Sci, Inst Computat Math & Sci Engn Comp, State Key Lab Sci & Engn Comp, Beijing 100080, Peoples R China
[2] Hong Kong Baptist Univ, Dept Math, Kowloon, Hong Kong, Peoples R China
基金
美国国家科学基金会;
关键词
unconstrained optimization; gradient method; R-linear convergence; strictly convex;
D O I
10.1093/imanum/22.1.1
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
Combined with non-monotone line search, the Barzilai and Borwein (BB) gradient method has been successfully extended for solving unconstrained optimization problems and is competitive with conjugate gradient methods. In this paper, we establish the R-linear convergence of the BB method for any-dimensional strongly convex quadratics. One corollary of this result is that the BB method is also locally R-linear convergent for general objective functions, and hence the stepsize in the BB method will always be accepted by the non-monotone line search when the iterate is close to the solution.
引用
收藏
页码:1 / 10
页数:10
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