Block factor-width-two matrices and their applications to semidefinite and sum-of-squares optimization
Semidefinite and sum-of-squares (SOS) optimization are fundamental computational tools in many areas, including linear and nonlinear systems theory. However, the scale of problems that can be addressed reliably and efficiently is still limited. In this paper, we introduce a new notion of block facto...
Auteurs principaux: | Zheng, Y, Sootla, A, Papachristodoulou, A |
---|---|
Format: | Journal article |
Langue: | English |
Publié: |
IEEE
2022
|
Documents similaires
-
Decomposed structured subsets for semidefinite and sum-of-squares optimization
par: Miller, J, et autres
Publié: (2022) -
Chordal and factor-width decompositions for scalable semidefinite and polynomial optimization
par: Zheng, Y, et autres
Publié: (2021) -
Decomposition and completion of sum-of-squares matrices
par: Zheng, Y, et autres
Publié: (2018) -
Equivariant Semidefinite Lifts and Sum-of-Squares Hierarchies
par: Fawzi, Hamza, et autres
Publié: (2016) -
Sparse sums of squares on finite abelian groups and improved semidefinite lifts
par: Fawzi, Hamza, et autres
Publié: (2016)