Tensor Approximation for Multidimensional and Multivariate Data

DOI10.1007/978-3-030-56215-1_4OpenAlexW3130613895MaRDI QIDQ6084502

Renato Pajarola, S. Suter, Rafael Ballester-Ripoll, Hai-yan Yang

Publication date: 30 November 2023

Published in: Mathematics and Visualization (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-030-56215-1_4

Mathematics Subject Classification ID

Computing methodologies for image processing (68U10) Computer graphics; computational geometry (digital and algorithmic aspects) (68U05) Multilinear algebra, tensor calculus (15A69)

Cites Work

• Unnamed Item
• Tensor Decompositions and Applications
• Sparse non-negative tensor factorization using columnwise coordinate descent
• Handwritten digit classification using higher order singular value decomposition
• Differential-geometric Newton method for the best rank-\((R _{1}, R _{2}, R _{3})\) approximation of tensors
• Some additional results on principal components analysis of three-mode data by means of alternating least squares algorithms
• Principal component analysis of three-mode data by means of alternating least squares algorithms
• Decomposition of quantics in sums of powers of linear forms
• An approach to n-mode components analysis
• Analysis of individual differences in multidimensional scaling via an \(n\)-way generalization of ``Eckart-Young decomposition
• A Newton–Grassmann Method for Computing the Best Multilinear Rank-$(r_1,$ $r_2,$ $r_3)$ Approximation of a Tensor
• A Multilinear Singular Value Decomposition
• On the Best Rank-1 and Rank-(R₁ ,R₂ ,. . .,R_N) Approximation of Higher-Order Tensors
• Mode-kn Factor Analysis for Image Ensembles
• Applied Multiway Data Analysis

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