Low-rank nonnegative tensor approximation via alternating projections and sketching

DOI10.1007/s40314-023-02211-2zbMath1505.65185arXiv2209.02060OpenAlexW4319078794MaRDI QIDQ2685220

Yanyan Li

Publication date: 20 February 2023

Published in: Computational and Applied Mathematics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2209.02060

zbMATH Keywords

sketchingalternating projectionslow-rank approximationTucker decompositionnonnegative tensorstensor train decomposition

Mathematics Subject Classification ID

Complexity and performance of numerical algorithms (65Y20) Multilinear algebra, tensor calculus (15A69) Randomized algorithms (68W20) Numerical methods for low-rank matrix approximation; matrix compression (65F55)

Related Items (5)

Sketching for a low-rank nonnegative matrix approximation: numerical study ⋮ NT-DPTC: a non-negative temporal dimension preserved tensor completion model for missing traffic data imputation ⋮ Study of performance of low-rank nonnegative tensor factorization methods ⋮ TR-STF: a fast and accurate tensor ring decomposition algorithm via defined scaled tri-factorization ⋮ Randomized low rank approximation for nonnegative pure quaternion matrices

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