Tensor approximation on fibre-crosses

L. Grasedyck, MPI Leipzig, Germany

Wednesday, May 6
at 16.15, HG E 1.2

In order to treat problems with tensors efficiently, one has to keep all data in a low rank format. The most efficient low rank format in terms of arithmetic complexity and storage requirements is the representation by elementary tensor sums. In this talk we will focus on the task to approximate a given high-dimensional tensor A by a low rank tensor X. Our goal is to find a good approximation X by sampling only very few entries of the tensor A. However, for tensors the construction of a low rank approximation by sampling only few points of A is a challenging task, both in terms of approximation quality and in terms of computational complexity. We present the state of the art and some numerical examples.