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 |
|---|---|
| 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
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