On the semidefinite representations of real functions applied to symmetric matrices

Please always quote using this URN: urn:nbn:de:0297-zib-17511
  • We present a new semidefinite representation for the trace of a real function f applied to symmetric matrices, when a semidefinite representation of the convex function f is known. Our construction is intuitive, and yields a representation that is more compact than the previously known one. We also show with the help of matrix geometric means and the Riemannian metric of the set of positive definite matrices that for a rational number p in the interval (0,1], the matrix X raised to the exponent p is the largest element of a set represented by linear matrix inequalities. We give numerical results for a problem inspired from the theory of experimental designs, which show that the new semidefinite programming formulation yields a speed-up factor in the order of 10.

Download full text files

Export metadata

Metadaten
Author:Guillaume Sagnol
Document Type:ZIB-Report
Volume:439
First Page:2829
Last Page:2843
Tag:SDP; matrix geometric mean; optimal experimental designs; semidefinite representability
MSC-Classification:90-XX OPERATIONS RESEARCH, MATHEMATICAL PROGRAMMING
CCS-Classification:G. Mathematics of Computing
Date of first Publication:2012/12/20
Series (Serial Number):ZIB-Report (12-50)
ISSN:1438-0064
Published in:Appear in: Linear Algebra and its Applications
DOI:https://doi.org/10.1016/j.laa.2013.08.021