Tuesday, May 11

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

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MMD, 12/21/98