John A. Hoffnagle, William D. Hinsberg, et al.
Microlithography 2003
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.
John A. Hoffnagle, William D. Hinsberg, et al.
Microlithography 2003
Hannaneh Hajishirzi, Julia Hockenmaier, et al.
UAI 2011
Harpreet S. Sawhney
IS&T/SPIE Electronic Imaging 1994
Ruixiong Tian, Zhe Xiang, et al.
Qinghua Daxue Xuebao/Journal of Tsinghua University