Study of performance of low-rank nonnegative tensor factorization methods
Author:
Affiliation:
1. Faculty of Computational Mathematics and Cybernetics, Lomonosov Moscow State University , Moscow , Russia .
2. Marchuk Insitute of Numerical Mathematics, Russian Academy of Sciences , Moscow , Russia
Abstract
Publisher
Walter de Gruyter GmbH
Subject
Modeling and Simulation,Numerical Analysis
Link
https://www.degruyter.com/document/doi/10.1515/rnam-2023-0018/pdf
Reference26 articles.
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2. N. Gillis, Nonnegative Matrix Factorization. SIAM, Philadelphia, 2020.
3. S. A. Goreinov, E. E. Tyrtyshnikov, and N. L. Zamarashkin, A theory of pseudoskeleton approximations. Linear Algebra and its Applications 261 (1997), No. 1-3, 1–21.
4. S. A. Goreinov and E. E. Tyrtyshnikov, The maximal-volume concept in approximation by low-rank matrices. Contemporary Mathematics 280 (2001), 47–52.
5. S. A. Goreinov, I. V. Oseledets, D. V. Savostyanov, E. E. Tyrtyshnikov, and N. L. Zamarashkin, How to find a good submatrix. In: Matrix Methods: Theory, Algorithms And Applications: Dedicated to the Memory of Gene Golub. World Scientific, 2010, pp. 247–256.
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