Monotonically convergent algorithms for symmetric tensor approximation

DOI10.1016/j.laa.2011.10.033zbMath1261.65043OpenAlexW2115139877MaRDI QIDQ1931773

Phillip A. Regalia

Publication date: 16 January 2013

Published in: Linear Algebra and its Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.laa.2011.10.033

zbMATH Keywords

stabilization methodpolar decompositiontensor approximationTucker productmonotonic convergencepower methodsconvex gradient inequality

Mathematics Subject Classification ID

Related Items (7)

Time integration of symmetric and anti-symmetric low-rank matrices and Tucker tensors ⋮ An equi-directional generalization of adaptive cross approximation for higher-order tensors ⋮ Random Projections for Low Multilinear Rank Tensors ⋮ Symmetric tensor decomposition by an iterative eigendecomposition algorithm ⋮ Numerical Computation for Orthogonal Low-Rank Approximation of Tensors ⋮ A Riemannian gradient ascent algorithm with applications to orthogonal approximation problems of symmetric tensors ⋮ Numerical optimization for symmetric tensor decomposition

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