Structured Semidefinite Programming for Recovering Structured Preconditioners Jerry Li Christopher Musco

Preconditioning is a fundamental primitive in the theory and practice of numerical linear algebra, optimization, and data science. Broadly, its goal is to improve conditioning properties (e.g., the range of eigenvalues) of a matrix M by finding another matrix N which approximates the inverse of M and is more efficient to construct and apply than computing M