On gradient based descent algorithms for joint diagonalization of matrices
Joint diagonalization of collections of matrices, i.e. the problem of finding a joint set of approximate eigenvectors, is an important problem that appears in many applicative contexts. It is commonly formulated as finding the minimizer, over the set of all possible bases, for a certain non-convex functional that measures the size of off-diagonal elements. Many approaches have been studied in the