Modified spectral PRP conjugate gradient method for solving tensor eigenvalue complementarity problems
DOI10.3934/jimo.2020147zbMath1499.90249OpenAlexW3088856170MaRDI QIDQ2076422
Ya Li, Shou-qiang Du, Yuan-Yuan Chen
Publication date: 16 February 2022
Published in: Journal of Industrial and Management Optimization (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.3934/jimo.2020147
unconstrained optimizationglobal convergencetensor eigenvalue complementarity problemPRP conjugate gradient method
Numerical mathematical programming methods (65K05) Nonlinear programming (90C30) Complementarity and equilibrium problems and variational inequalities (finite dimensions) (aspects of mathematical programming) (90C33) Eigenvalues, singular values, and eigenvectors (15A18)
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Cites Work
- Positive-definite tensors to nonlinear complementarity problems
- Higher-degree eigenvalue complementarity problems for tensors
- Tensor complementarity problem and semi-positive tensors
- Global uniqueness and solvability for tensor complementarity problems
- Properties of solution set of tensor complementarity problem
- A semismooth Newton method for tensor eigenvalue complementarity problem
- Symmetric nonnegative tensors and copositive tensors
- On restart procedures for the conjugate gradient method
- New spectral PRP conjugate gradient method for unconstrained optimization
- On prescribing the convergence behavior of the conjugate gradient algorithm
- Tensor eigenvalue complementarity problems
- Spectral projected gradient methods for generalized tensor eigenvalue complementarity problems
- Tensor eigenvalues and their applications
- Global uniqueness and solvability of tensor complementarity problems for \(\mathcal{H}_+\)-tensors
- Family weak conjugate gradient algorithms and their convergence analysis for nonconvex functions
- Tensor complementarity problems. I: Basic theory
- Tensor complementarity problems. II: Solution methods
- Tensor complementarity problems. III: Applications
- Two families of scaled three-term conjugate gradient methods with sufficient descent property for nonconvex optimization
- Stochastic structured tensors to stochastic complementarity problems
- A potential reduction method for tensor complementarity problems
- Global error bounds for the tensor complementarity problem with a \(P\)-tensor
- A quadratically convergent algorithm for finding the largest eigenvalue of a nonnegative homogeneous polynomial map
- Properties of some classes of structured tensors
- A new method for solving Pareto eigenvalue complementarity problems
- A mixed integer programming approach to the tensor complementarity problem
- Global convergence of a modified Fletcher-Reeves conjugate gradient method with Armijo-type line search
- \(M\)-tensors and nonsingular \(M\)-tensors
- Eigenvalues of a real supersymmetric tensor
- A family of three-term conjugate gradient methods with sufficient descent property for unconstrained optimization
- On eigenvalue problems of real symmetric tensors
- Exceptionally regular tensors and tensor complementarity problems
- $M$-Tensors and Some Applications
- Quadratic Eigenvalue Problems under Conic Constraints
- Shifted Power Method for Computing Tensor Eigenpairs
- Finding the Largest Eigenvalue of a Nonnegative Tensor
- Properties of Tensor Complementarity Problem and Some Classes of Structured Tensors
- A Nonlinear Conjugate Gradient Method with a Strong Global Convergence Property
- Generalized Eigenvalue Complementarity Problem for Tensors
- Tensor Analysis
- Stability of Solutions and Continuity of Solution Maps of Tensor Complementarity Problems
- A spectral conjugate gradient method for unconstrained optimization
- On the cone eigenvalue complementarity problem for higher-order tensors
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