This workshop is part of the triennial FoCM conference series, organized by the Society for Foundations of Computational Mathematics.
This workshop focuses on five topics currently very active inside Numerical Linear Algebra as a consequence of their multiple applications and the challenging computational and theoretical problems they pose. These topics are Tensor Computations, Optimal Distance Matrix Problems, Algorithms for solving Matrix Equations, Nonlinear Eigenvalue Problems, and recent advances on High Performance Computing related to these and other problems. These topics have in common the necessity of using compressed representations or approximations in order to be able to store the large amount of data involved in the solutions of the corresponding problems and to develop efficient algorithms that work on these representations, which are often related to low rank approximations. In addition, the solution of these problems involves very often optimization techniques applied to nontrivial matrix magnitudes. This workshop brings together a group of leading experts, ranging from brilliant early-career researchers to well-established senior researchers, in the computational and theoretical aspects of these topics.
Schedule and talk abstracts: here
Related plenary talk: TBA
Related workshops of FoCM'17: Approximation Theory, Random Matrices, Multiresolution and Adaptivity in Numerical PDEs, Computational Harmonic Analysis and Compressive Sensing, Foundations of Numerical PDEs