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ALOP Colloquium with Prof. Dr. Lars Grasedyck
4. October 2016 / 15:45 - 17:45
will join the ALOP-Colloquium and present his recent work. At 15:45 there will be a coffee hour in E10. At 16:15 the presentation will take place in HS9.
Hierarchical Low Rank Tensor Formats
The first part of this talk on hierarchical low rank formats starts with a general introduction to notions of rank in higher dimensions, namely Canonical Polyadic (CP), Tucker, TT and Hierarchical Tucker (HT) ranks and the corresponding data-sparse tensor representations.
Each of the notions of rank gives rise to a different set or manifold of tensors of fixed rank and we compare very briefly the advantages and drawbacks between the different formats. The concepts are introduced in the discrete setting where a tensor is a mapping from a d-fold Cartesian product of finite index sets, but we also point out the relation to d-variate functions, the continuous setting. We summarize some interesting open questions that open new and sometimes very difficult areas of research.
In the second (and shorter) part of the talk we consider the application of hierarchical low rank formats for uncertainty quantification, or more specifically for the data-sparse representation of parameter dependent quantities of interest. The data-sparse low rank formats have a strong relation to reduced basis techniques for linear and nonlinear model reduction, but both methods have their individual advantages or disadvantages. The most challenging question in this area is whether or not the object of interest possesses the low rank structure and how one can reliably approximate it.