Computing the best rank-(R_1,R_2,R_3) approximation of a tensor


Lars Eldén
joint work with Berkant Savas

We discuss various properties of the best rank-(R_1,R_2,R_3) approximation of a tensor, and their implications in the development of algorithms for computing the approximation. In particular we discuss the Grassmann-Newton method for solving the problem, and its relation to the Grassmann-Rayleigh quotient iteration of de Lathauwer et al.