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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.
The workshop will include five invited talks and several contributed talks. We encourage all participants to propose a talk in order to share their results, research problems and goals.
Invited speakers:
Important dates:
Organizing committee
Please contact the organisers at smd2019@listes.math.cnrs.fr if you have any question.