Semismooth matrix-valued functions

被引:173
|
作者
Sun, DF
Sun, X
机构
[1] Natl Univ Singapore, Dept Math, Singapore 117548, Singapore
[2] Natl Univ Singapore, Fac Business Adm, Singapore 117548, Singapore
[3] Natl Univ Singapore, Singapore MIT Alliance, Singapore 117548, Singapore
关键词
matrix functions; Newton's method; nonsmooth optimization; semidefinite programming;
D O I
10.1287/moor.27.1.150.342
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
Matrix-valued functions play an important role in the development of algorithms for semidefinite programming problems. This paper studies generalized differential properties of such functions related to nonsmooth-smoothing Newton methods. The first part of this paper discusses basic properties such as the generalized derivative, Rademacher's theorem, B-derivative, directional derivative, and semismoothness. The second part shows that the matrix absolute-value function, the matrix semidefinite-projection function, and the matrix projective residual function are strongly semismooth.
引用
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页码:150 / 169
页数:20
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