Matrices that arise from a large range of problems in mathematics, physics, engineering etc. typically display a characteristic structure, such as sparsity patterns or a rank structure (e.g., quasi/semi-separable, Toeplitz-like etc. ). Exploiting this structure is the key to the design of more efficient algorithms.
The study of structured matrices is an interdisciplinary field that places itself at a crossroads between symbolic computation (uni- and multivariate polynomial computation, matrix polynomials...), numerical linear algebra (solution of linear systems, classical and generalized eigenvalue problems, functions of matrices...), and more generally all applications that involve structured problems. We aim to provide an opportunity for researchers from several fields to present their results, exchange ideas, develop and improve collaborations.
- Stefano Massei (École Polytechnique Fédérale Lausanne)
- José Henrique de Morais Goulart (GIPSA-lab, CNRS, Grenoble)
- Françoise Tisseur (University of Manchester)