Decomposed structured subsets for semidefinite and sum-of-squares optimization
Decomposed structured subsets for semidefinite and sum-of-squares optimization is a scholarly work by Yang Zheng, published in 2022 in ''Automatica''. The main subjects of the publication include combinatorics, mathematics, interior point method, mathematical optimization, upper and lower bounds, optimization problem, Explained sum of squares, diagonal, compressed sensing, norm, convex optimization, Semidefinite embedding, iterative numerical method, quadratically constrained quadratic program, regular polygon, polynomial, semidefinite programming, and definite matrix. The authors present a notion of decomposed structured\nsubsets}to approximate an SDP with structured subsets after an equivalent\nconversion.