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Regularization Methods for SDP Relaxations in Large Scale Polynomial Optimization

Li Wang


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