[Home]
[
News]
[ Events]
[ People]
[ Research]
[ Education]
[Visitor Info]
[UCSD Only]
[Admin]
Regularization Methods for SDP Relaxations in Large Scale Polynomial Optimization
Li Wang
UCSD
Abstract:
The talk will review semidefinite programming (SDP) relaxations for polynomial optimization and show how to solve them. We propose regularization type methods to solve such large scale SDP problems. Significantly bigger problems would be solved, which is not possible by using prior existing methods like interior-point algorithms. Numerical examples will also be shown.
Tuesday, February 22, 2011
11:00AM AP&M 2402
News]
[ Events]
[ People]
[ Research]
[ Education]
[Visitor Info]
[UCSD Only]
[Admin]
Directors:
Randolph E. Bank
Philip E. Gill
Michael Holst
Administrative Contact:
[ Click to Send Email ]
Randolph E. Bank
Philip E. Gill
Michael Holst
Administrative Contact:
[ Click to Send Email ]
Li Wang
UCSD
Abstract:
The talk will review semidefinite programming (SDP) relaxations for polynomial optimization and show how to solve them. We propose regularization type methods to solve such large scale SDP problems. Significantly bigger problems would be solved, which is not possible by using prior existing methods like interior-point algorithms. Numerical examples will also be shown.
Tuesday, February 22, 2011
11:00AM AP&M 2402