5 papers
A geodesic convexity-like structure for the polar decomposition of a square matrix
Foivos Alimisis, Bart Vandereycken
We make a full landscape analysis of the (generally non-convex) orthogonal Procrustes problem. This problem is equivalent to computing the polar factor of a square matrix. We revea…
A preconditioned inverse iteration with an improved convergence guarantee
Foivos Alimisis, Daniel Kressner, Nian Shao +1
Preconditioned eigenvalue solvers offer the possibility to incorporate preconditioners for the solution of large-scale eigenvalue problems, as they arise from the discretization of…
A Nesterov-style Accelerated Gradient Descent Algorithm for the Symmetric Eigenvalue Problem
Foivos Alimisis, Simon Vary, Bart Vandereycken
We develop an accelerated gradient descent algorithm on the Grassmann manifold to compute the subspace spanned by a number of leading eigenvectors of a symmetric positive semi-defi…
Characterization of optimization problems that are solvable iteratively with linear convergence
Foivos Alimisis
In this work, we state a general conjecture on the solvability of optimization problems via algorithms with linear convergence guarantees. We make a first step towards examining it…
Gradient-type subspace iteration methods for the symmetric eigenvalue problem
Foivos Alimisis, Yousef Saad, Bart Vandereycken
This paper explores variants of the subspace iteration algorithm for computing approximate invariant subspaces. The standard subspace iteration approach is revisited and new varian…