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Semismooth matrix-valued functions

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Abstract
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.
Keywords
Matrix functions, Newton's method, Nonsmooth optimization, Semidefinite programming
Source Title
Mathematics of Operations Research
Publisher
Series/Report No.
Organizational Units
Organizational Unit
DECISION SCIENCES
dept
Organizational Unit
MATHEMATICS
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Rights
Date
2002
DOI
Type
Article
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