Tuesday, May 11
MS24
Software and Algorithms for Semidefinite Optimization
3:30 PM-5:30 PM
Room: Capitol Center
Semidefinite optimization is a young, fast developing field of
optimization theory. SDO has many important applications. Many
research groups are active by developing efficient research codes to
solve semidefinite optimization problems. The speakers inf this
minisymposium will provide an overview of the state of the art, and
what is needed to design an efficient implementation of
interior-point algorithms for semidefinite optimization.
Organizer: Tamás Terlaky
Delft University of Technology, The Netherlands
- 3:30-3:55 Sparse Matrices and Numerical Stability in Convex
Quadratically Constrained Optimization
- Fahrid Alizadeh and Stefan Schmieta, Rutgers University
- 4:00-4:25 SDPA: The Optimization Software for the Semidefinite Programs
- Katsuki Fujisawa, Kyoto University, Japan; Masakazu
Kojima, Tokyo Institute of Technology, Japan; and Kazuhide Nakata,
Nihon Sun Microsystems K. K., Tokyo, Japan
- 4:30-4:55 CSDP - A C Library for Semidefinite Programming
- Brian Borchers, New Mexico Institute of Mining & Technology
- 5:00-5:25 An Efficient Algorithm for Solving the Maximum Cut
Relaxation SDP Problem
- Renato D. C. Monteiro and Samuel Burer, Georgia
Institute of Technology
MMD, 12/21/98