Rank-1 Tensor Properties with Applications to a Class of Tensor Optimization Problems

DOI10.1137/140983689zbMath1329.90114OpenAlexW2262986604MaRDI QIDQ3465242

Yuning Yang, Yun-Long Feng, Johan A. K. Suykens, Xiao Lin Huang

Publication date: 21 January 2016

Published in: SIAM Journal on Optimization (Search for Journal in Brave)

Full work available at URL: https://lirias.kuleuven.be/handle/123456789/515906

zbMATH Keywords

convex relaxationnuclear normhigher order tensorrank-1 approximationbalanced unfoldingrank-1 equivalence property

Mathematics Subject Classification ID

Nonconvex programming, global optimization (90C26) Best approximation, Chebyshev systems (41A50) Eigenvalues, singular values, and eigenvectors (15A18) Multilinear algebra, tensor calculus (15A69)

Related Items (9)

Convergence rate analysis for the higher order power method in best rank one approximations of tensors ⋮ On approximation algorithm for orthogonal low-rank tensor approximation ⋮ Several approximation algorithms for sparse best rank-1 approximation to higher-order tensors ⋮ An approximation method of CP rank for third-order tensor completion ⋮ Some inequalities on the spectral radius of nonnegative tensors ⋮ The low-rank approximation of fourth-order partial-symmetric and conjugate partial-symmetric tensor ⋮ On decompositions and approximations of conjugate partial-symmetric tensors ⋮ A locally convergent Jacobi iteration for the tensor singular value problem ⋮ Computing the largest C-eigenvalue of a tensor using convex relaxation

Uses Software

• TensorToolbox
• Tensorlab

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