Structured Matrix Problems from Tensors
From MaRDI portal
Publication:2971624
DOI10.1007/978-3-319-49887-4_1zbMath1361.65024OpenAlexW2585152245MaRDI QIDQ2971624
Publication date: 7 April 2017
Published in: Lecture Notes in Mathematics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/978-3-319-49887-4_1
Numerical solutions to overdetermined systems, pseudoinverses (65F20) Multilinear algebra, tensor calculus (15A69)
Related Items (5)
Scalable tensor-product preconditioners for high-order finite-element methods: scalar equations ⋮ On global iterative schemes based on Hessenberg process for (ill-posed) Sylvester tensor equations ⋮ Nonlinear power-like iteration by polar decomposition and its application to tensor approximation ⋮ Multilinear Control Systems Theory ⋮ Low-rank approximation to entangled multipartite quantum systems
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Tensor Decompositions and Applications
- TT-cross approximation for multidimensional arrays
- A Schur decomposition for Hamiltonian matrices
- The ubiquitous Kronecker product
- Block tensors and symmetric embeddings
- Tensor-product approximation to operators and functions in high dimensions
- On the Best Rank-1 Approximation of Higher-Order Supersymmetric Tensors
- Block Tensor Unfoldings
- Breaking the Curse of Dimensionality, Or How to Use SVD in Many Dimensions
- Elemental
- Algorithm 862
- The vec-permutation matrix, the vec operator and Kronecker products: a review
- A Multilinear Singular Value Decomposition
- Numerical operator calculus in higher dimensions
- Approximating Matrices with Multiple Symmetries
- Tensor Rank and the Ill-Posedness of the Best Low-Rank Approximation Problem
- A Jacobi-Type Method for Computing Orthogonal Tensor Decompositions
- Symmetric Tensors and Symmetric Tensor Rank
- Most Tensor Problems Are NP-Hard
- Algorithms for Numerical Analysis in High Dimensions
This page was built for publication: Structured Matrix Problems from Tensors