Fast Nonnegative Tensor Factorizations with Tensor Train Model

Fast Nonnegative Tensor Factorizations with Tensor Train Model

Tensor train model is a low-rank approximation for multidimensional data. In this article we demonstrate how it can be succesfully used for fast computation of nonnegative tensor train, nonnegative canonical and nonnegative Tucker factorizations. The proposed approaches can be incorporated in wide r...

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Veröffentlicht in:Lobachevskii journal of mathematics 2022-04, Vol.43 (4), p.882-894
Hauptverfasser: Shcherbakova, E. M., Tyrtyshnikov, E. E.
Format: Artikel
Sprache:eng
Schlagworte:
Algebra
Analysis
Big Data
Geometry
Mathematical analysis
Mathematical Logic and Foundations
Mathematics
Mathematics and Statistics
Multidimensional data
Probability Theory and Stochastic Processes
Tensors
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Zusammenfassung:Tensor train model is a low-rank approximation for multidimensional data. In this article we demonstrate how it can be succesfully used for fast computation of nonnegative tensor train, nonnegative canonical and nonnegative Tucker factorizations. The proposed approaches can be incorporated in wide range of methods to solve big data problems.
ISSN:1995-0802
1818-9962
DOI:10.1134/S1995080222070228