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.
Original language | English |
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Pages (from-to) | 150-169 |
Number of pages | 20 |
Journal | Mathematics of Operations Research |
Volume | 27 |
Issue number | 1 |
DOIs | |
Publication status | Published - 1 Jan 2002 |
Externally published | Yes |
Keywords
- Matrix functions
- Newton's method
- Nonsmooth optimization
- Semidefinite programming
ASJC Scopus subject areas
- General Mathematics
- Computer Science Applications
- Management Science and Operations Research