Exploiting sparsity in the coefficient matching conditions in sum-of-squares programming using ADMM
This letter introduces an efficient first-order method based on the alternating direction method of multipliers (ADMM) to solve semidefinite programs arising from sum-of-squares (SOS) programming. We exploit the sparsity of the coefficient matching conditions when SOS programs are formulated in the...
Huvudupphovsmän: | Zheng, Y, Fantuzzi, G, Papachristodoulou, A |
---|---|
Materialtyp: | Journal article |
Publicerad: |
IEEE
2017
|
Liknande verk
-
Fast ADMM for sum-of-squares programs using partial orthogonality
av: Zheng, Y, et al.
Publicerad: (2018) -
Fast ADMM for semidefinite programs with chordal sparsity
av: Zheng, Y, et al.
Publicerad: (2017) -
Decomposition and completion of sum-of-squares matrices
av: Zheng, Y, et al.
Publicerad: (2018) -
Sparse sum-of-squares (SOS) optimization: A bridge between DSOS/SDSOS and SOS optimization for sparse polynomials
av: Zheng, Y, et al.
Publicerad: (2019) -
Fast ADMM for homogeneous self-dual embeddings of sparse SDPs
av: Zheng, Y, et al.
Publicerad: (2016)