The last few years have seen a tremendous increase in the use of low rank matrix and tensor approximation techniques for solving tasks in scientific computing and data analysis. These developments have resulted in new algorithms capable of solving linear algebra problems whose sheer size renders the use of traditional approaches infeasible. The aim of this talk is to give a survey of this exciting research direction and point out the many challenging questions that remain. This will be illustrated with several examples, including the solution of high-dimensional partial differential equations and tensor completion for fitting incomplete data.

Referent: Professor Dr. Daniel Kressner, EPFL Lausanne

Zuvor gibt es ab 16:45 Uhr die Gelegenheit, die Sprecherin oder den Sprecher beim Kolloquiumstee in Gebäude 48, Raum 538 zu treffen.