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Preprint-No.: <   392   >   Published in: April 2014   PDF-File: IGPM392.pdf
Title:Sampling Rules for Tensor Reconstruction in Hierarchical Tucker Format
Authors:Melanie Kluge
The subject of this article is the development of an algorithm that re- constructs a high-dimensional tensor by a hierarchical (H-) Tucker tensor with the help of a non-adaptive sampling rule. This sampling rule supports our approximation scheme coming from the matrix cross approximation and guarantees that we can build a tensor AH in the desired format from only a few entries of the original tensor A. Under mild assumptions AH is a reconstruction of A. In the numerical experiments we obtain convenient approximations also for tensors without low rank representation and for per- tubed tensors.
Keywords:tensor completion, tensor approximation, tensor train