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math.OC2019
A Note on Convex Relaxations for the Inverse Eigenvalue Problem
Utkan Candogan, Yong Sheng Soh, Venkat Chandrasekaran
The affine inverse eigenvalue problem consists of identifying a real symmetric matrix with a prescribed set of eigenvalues in an affine space. Due to its ubiquity in applications,…
math.OC2019★ 34 cited
Signomial and Polynomial Optimization via Relative Entropy and Partial Dualization
Riley Murray, Venkat Chandrasekaran, Adam Wierman
We describe a generalization of the Sums-of-AM/GM Exponential (SAGE) relaxation methodology for obtaining bounds on constrained signomial and polynomial optimization problems. Our…