On the Convergence of Alternating Least Squares Optimisation in Tensor Format Representations

Mike Espig; Wolfgang Hackbusch; Aram Khachatryan

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arXiv · 1506.00062

On the Convergence of Alternating Least Squares Optimisation in Tensor Format Representations

Mike Espig·Wolfgang Hackbusch·Aram Khachatryan

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Abstract

The approximation of tensors is important for the efficient numerical treatment of high dimensional problems, but it remains an extremely challenging task. One of the most popular approach to tensor approximation is the alternating least squares method. In our study, the convergence of the alternating least squares algorithm is considered. The analysis is done for arbitrary tensor format representations and based on the multiliearity of the tensor format. In tensor format representation techniques, tensors are approximated by multilinear combinations of objects lower dimensionality. The resulting reduction of dimensionality not only reduces the amount of required storage but also the computational effort.

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Mike Espig, Wolfgang Hackbusch, Aram Khachatryan. 2015-05-30. On the Convergence of Alternating Least Squares Optimisation in Tensor Format Representations. https://arxiv.org/abs/1506.00062

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