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- research-articleJuly 2022
Algorithms for Testing Membership in Univariate Quadratic Modules over the Reals
ISSAC '22: Proceedings of the 2022 International Symposium on Symbolic and Algebraic ComputationPages 429–437https://doi.org/10.1145/3476446.3536176Quadratic modules in real algebraic geometry are akin to polynomial ideals in algebraic geometry, and have been found useful in the theory of Positivstellensatz to study Hilbert's 17th problem. Algorithms are presented in this paper for testing ...
- articleAugust 2013
An Exact Duality Theory for Semidefinite Programming Based on Sums of Squares
Mathematics of Operations Research (MOOR), Volume 38, Issue 3Pages 569–590https://doi.org/10.1287/moor.1120.0584Farkas' lemma is a fundamental result from linear programming providing linear certificates for infeasibility of systems of linear inequalities. In semidefinite programming, such linear certificates only exist for strongly infeasible linear matrix ...
- articleMarch 2010
Exposed Faces of Semidefinitely Representable Sets
SIAM Journal on Optimization (SIOPT), Volume 20, Issue 4Pages 1944–1955A linear matrix inequality (LMI) is a condition stating that a symmetric matrix whose entries are affine-linear combinations of variables is positive semidefinite. Motivated by the fact that diagonal LMIs define polyhedra, the solution set of an LMI is ...
- tutorialJuly 2009
Describing convex semialgebraic sets by linear matrix inequalities
ISSAC '09: Proceedings of the 2009 international symposium on Symbolic and algebraic computationPages 385–386https://doi.org/10.1145/1576702.1576756A semialgebraic set is a set described by a boolean combination of real polynomial inequalities in several variables. A linear matrix inequality (LMI) is a condition expressing that a symmetric matrix whose entries are affine-linear combinations of ...