An adaptive gradient method for computing generalized tensor eigenpairs
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Publication:2374369
DOI10.1007/s10589-016-9846-9zbMath1357.90154arXiv1601.01399OpenAlexW2294557853MaRDI QIDQ2374369
Publication date: 15 December 2016
Published in: Computational Optimization and Applications (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1601.01399
Related Items (13)
Riemannian conjugate gradient methods for computing the extreme eigenvalues of symmetric tensors ⋮ Local convergence analysis of inverse iteration algorithm for computing the H-spectral radius of a nonnegative weakly irreducible tensor ⋮ A family of gradient methods using Householder transformation with application to hypergraph partitioning ⋮ Noda iteration for computing generalized tensor eigenpairs ⋮ Feasible Newton methods for symmetric tensor Z-eigenvalue problems ⋮ Calculations for D-eigenvalues of a diffusion kurtosis tensor ⋮ Calculating entanglement eigenvalues for nonsymmetric quantum pure states based on the Jacobian semidefinite programming relaxation method ⋮ Spectral projected gradient methods for generalized tensor eigenvalue complementarity problems ⋮ Computing the generalized eigenvalues of weakly symmetric tensors ⋮ Computing the largest H-eigenvalue of large-scale tensors generated from directed hypergraphs ⋮ A hybrid second-order method for homogenous polynomial optimization over unit sphere ⋮ Iterative methods for computing U-eigenvalues of non-symmetric complex tensors with application in quantum entanglement ⋮ A generalization of inverse power method for computing eigenpairs of symmetric tensors
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