On the relation between the AINV and the FAPINV algorithms.
On the set of weighted least squares solutions of systems of convex inequalities
On the Sharpness of Some Upper Bounds for the Spectral Radii of S.O.R. Iteration Matrices.
On the shifted QR iteration applied to companion matrices.
On the singular two-parameter eigenvalue problem.
On the solution of Cauchy systems of equations.
On the solution of multiparameter problems of algebra. IV: The algorithm and its applications.
On the solution of multiparameter problems of algebra. V: The - factorization algorithm and its applications.
On the Solution of Singular Linear Systems of Algebraic Equations by Semiiterative Methods.
On the Stability of Finite Numerical Procedures.
On the subspace projected approximate matrix method
We provide a comparative study of the Subspace Projected Approximate Matrix method, abbreviated SPAM, which is a fairly recent iterative method of computing a few eigenvalues of a Hermitian matrix . It falls in the category of inner-outer iteration methods and aims to reduce the costs of matrix-vector products with within its inner iteration. This is done by choosing an approximation of , and then, based on both and , to define a sequence of matrices that increasingly better approximate...
On the trace characterization of the joint spectral radius.
On the use of larger bulges in the QR algorithm.
On the worst-case convergence of MR and CG for symmetric positive definite tridiagonal Toeplitz matrices.
On theoretical and practical acceleration of randomized computation of the determinant of an integer matrix.
On Transformations of Graded Matrices, with Applications to Stiff ODE's.
On Updating Triangular Products of Householder Reflections.
On worst-case GMRES, ideal GMRES, and the polynomial numerical hull of a Jordan block.
One-sided simultaneous inequalities and sandwich theorems for diagonal similarity and diagonal equivalence of nonnegative matrices.
Operator preconditioning with efficient applications for nonlinear elliptic problems
This paper is devoted to the numerical solution of nonlinear elliptic partial differential equations. Such problems describe various phenomena in science. An approach that exploits Hilbert space theory in the numerical study of elliptic PDEs is the idea of preconditioning operators. In this survey paper we briefly summarize the main lines of this theory with various applications.