Michael E. Henderson
International Journal of Bifurcation and Chaos in Applied Sciences and Engineering
Our interest lies in solving sum of squares (SOS) relaxations of large-scale unconstrained polynomial optimization problems. Because interior-point methods for solving these problems are severely limited by the large-scale, we are motivated to explore efficient implementations of an accelerated first-order method to solve this class of problems. By exploiting special structural properties of this problem class, we greatly reduce the computational cost of the first-order method at each iteration. We report promising computational results as well as a curious observation about the behaviour of the first-order method for the SOS relaxations of the unconstrained polynomial optimization problem. © 2013 Copyright Taylor and Francis Group, LLC.
Michael E. Henderson
International Journal of Bifurcation and Chaos in Applied Sciences and Engineering
Charles A Micchelli
Journal of Approximation Theory
Corneliu Constantinescu
SPIE Optical Engineering + Applications 2009
William Hinsberg, Joy Cheng, et al.
SPIE Advanced Lithography 2010