Furthermore, we reformulate within the framework of flexible Krylov methods both the new innerouter methods for nuclear norm regularization and some of the existing Krylov methods incorporating low-rank projections. This results in an even more computationally efficient (but heuristic) strategy that ...
A fast rank-reduction algorithm for three-dimensional seismic data interpolation 2016, Journal of Applied Geophysics Citation Excerpt : Many efficient methods in the context of matrix completion are employed to solve the computation problem of SVD. Stoll (2012) computes partial SVD through a Krylov ...
rank(A) X i=1 u T i b ¾ i v i : Regularized solutions (obtained by \spectral ¯ltering") are: x reg = n X i=1 ' i u T i b ¾ i v i ; ' i = ¯lter factors: Augus t 2014 11/ 61 P . C. Ha n s e n – Kr y lo v Su b s p a c e Me t h o...
In the next section, we will define the GA for solving Stein matrix equations. 3. Galerkin-Based Methods In this section, we will apply the Galerkin projection method to obtain low-rank approximate solutions of the nonsymmetric Stein matrix Equation (1). This approach has been applied for ...
Keywords: extended block Krylov subspaces; low-rank approximation; Stein matrix equation; Galerkin approach (GA); minimal residual (MR) methods 1. Introduction In this paper, we are interested in the numerical solution of large scale nonsymmetric Stein matrix equations of the form: AXB − X +...