An Interior-Point Method for Semidefinite Programming
SIAM Journal on Optimization1996Vol. 6(2), pp. 342–361
Citations Over TimeTop 1% of 1996 papers
Abstract
We propose a new interior-point-based method to minimize a linear function of a matrix variable subject to linear equality and inequality constraints over the set of positive semidefinite matrices. We show that the approach is very efficient for graph bisection problems such as max–cut. Other applications include max–min eigenvalue problems and relaxations for the stable set problem.
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