Finding the maximum eigenvalue of essentially nonnegative symmetric tensors via sum of squares programming
From MaRDI portal
Publication:378284
DOI10.1007/s10957-013-0293-9zbMath1274.90258OpenAlexW1999536991WikidataQ59241496 ScholiaQ59241496MaRDI QIDQ378284
Liqun Qi, Yisheng Song, Guoyin Li, Sheng-Long Hu
Publication date: 11 November 2013
Published in: Journal of Optimization Theory and Applications (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s10957-013-0293-9
Related Items (18)
A tensor analogy of Yuan's theorem of the alternative and polynomial optimization with sign structure ⋮ An adaptive gradient method for computing generalized tensor eigenpairs ⋮ Pseudo-spectra theory of tensors and tensor polynomial eigenvalue problems ⋮ A survey on the spectral theory of nonnegative tensors ⋮ The Z -eigenvalues of a symmetric tensor and its application to spectral hypergraph theory ⋮ Computing the dominant eigenpair of an essentially nonnegative tensor via a homotopy method ⋮ \(p\)-norm \(B\)-tensors and \(p\)-norm \(B_0\)-tensors ⋮ The location of H-eigenvalues of real even order symmetry tensors ⋮ A MODIFIED FR CONJUGATE GRADIENT METHOD FOR COMPUTING -EIGENPAIRS OF SYMMETRIC TENSORS ⋮ Positive definiteness for 4th order symmetric tensors and applications ⋮ On the uniqueness of the positive Z-eigenvector for nonnegative tensors ⋮ Further results on Cauchy tensors and Hankel tensors ⋮ Computing the generalized eigenvalues of weakly symmetric tensors ⋮ New iterative criteria for strong \(\mathcal{H}\)-tensors and an application ⋮ The Laplacian of a uniform hypergraph ⋮ On computing minimal \(H\)-eigenvalue of sign-structured tensors ⋮ Approximation algorithms for nonnegative polynomial optimization problems over unit spheres ⋮ Unnamed Item
Uses Software
Cites Work
- Unnamed Item
- Tensor Decompositions and Applications
- Necessary and sufficient conditions for \(S\)-lemma and~nonconvex quadratic optimization
- Global quadratic minimization over bivalent constraints: necessary and sufficient global optimality condition
- Necessary global optimality conditions for nonlinear programming problems with polynomial constraints
- Positive semidefinite diagonal minus tail forms are sums of squares
- An always convergent algorithm for the largest eigenvalue of an irreducible nonnegative tensor
- Perron-Frobenius theorem for nonnegative tensors
- Multivariate polynomial minimization and its application in signal processing
- Semidefinite programming relaxations for semialgebraic problems
- Algebraic connectivity of an even uniform hypergraph
- Perron-Frobenius theorem for nonnegative multilinear forms and extensions
- Semismoothness of the maximum eigenvalue function of a symmetric tensor and its application
- Exact SDP relaxations for classes of nonlinear semidefinite programming problems
- Global error bounds for piecewise convex polynomials
- Eigenvalues of a real supersymmetric tensor
- On eigenvalue problems of real symmetric tensors
- Global Optimization with Polynomials and the Problem of Moments
- On the Best Rank-1 Approximation of Higher-Order Supersymmetric Tensors
- The dominant eigenvalue of an essentially nonnegative tensor
- The Z -eigenvalues of a symmetric tensor and its application to spectral hypergraph theory
- On the Asymptotically Well Behaved Functions and Global Error Bound for Convex Polynomials
- Further Results for Perron–Frobenius Theorem for Nonnegative Tensors
- Primitivity, the Convergence of the NQZ Method, and the Largest Eigenvalue for Nonnegative Tensors
- Further Results for Perron–Frobenius Theorem for Nonnegative Tensors II
- Alternative Theorems for Quadratic Inequality Systems and Global Quadratic Optimization
- Finding the Largest Eigenvalue of a Nonnegative Tensor
- On the Best Rank-1 and Rank-(R1 ,R2 ,. . .,RN) Approximation of Higher-Order Tensors
- Semidefinite Programming
- Linear Convergence of the LZI Algorithm for Weakly Positive Tensors
- Linear convergence of an algorithm for computing the largest eigenvalue of a nonnegative tensor
- An Eigenvalue Method for Testing Positive Definiteness of a Multivariate Form
- Pre- and Post-Processing Sum-of-Squares Programs in Practice
- Higher Order Positive Semidefinite Diffusion Tensor Imaging
This page was built for publication: Finding the maximum eigenvalue of essentially nonnegative symmetric tensors via sum of squares programming
