A family of gradient methods using Householder transformation with application to hypergraph partitioning
DOI10.1007/s11075-023-01593-yOpenAlexW4382515338MaRDI QIDQ6140902
Jingya Chang, Xin Zhang, Zhou Sheng, Zhili Ge
Publication date: 22 January 2024
Published in: Numerical Algorithms (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s11075-023-01593-y
Numerical computation of eigenvalues and eigenvectors of matrices (65F15) Numerical optimization and variational techniques (65K10) Computing methodologies for image processing (68U10) Graph theory (including graph drawing) in computer science (68R10) Numerical aspects of computer graphics, image analysis, and computational geometry (65D18)
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- A modified Hestenes and Stiefel conjugate gradient algorithm for large-scale nonsmooth minimizations and nonlinear equations
- The largest \(H\)-eigenvalue and spectral radius of Laplacian tensor of non-odd-bipartite generalized power hypergraphs
- Spectra of uniform hypergraphs
- \(H^{+}\)-eigenvalues of Laplacian and signless Laplacian tensors
- Laplacian and signless Laplacian Z-eigenvalues of uniform hypergraphs
- Efficient generalized conjugate gradient algorithms. I: Theory
- Computing the \(p\)-spectral radii of uniform hypergraphs with applications
- Algebraic connectivity of an even uniform hypergraph
- Family weak conjugate gradient algorithms and their convergence analysis for nonconvex functions
- The Laplacian of a uniform hypergraph
- The global convergence of the Polak-Ribière-Polyak conjugate gradient algorithm under inexact line search for nonconvex functions
- A quadratically convergent algorithm for finding the largest eigenvalue of a nonnegative homogeneous polynomial map
- Circulant tensors with applications to spectral hypergraph theory and stochastic process
- An adaptive gradient method for computing generalized tensor eigenpairs
- Computing extreme eigenvalues of large scale Hankel tensors
- Eigenvalues of a real supersymmetric tensor
- A modified conjugate gradient method for general convex functions
- On the Best Rank-1 Approximation of Higher-Order Supersymmetric Tensors
- Computing Tensor Eigenvalues via Homotopy Methods
- Spectral directed hypergraph theory via tensors
- Computing Eigenvalues of Large Scale Sparse Tensors Arising from a Hypergraph
- The Z -eigenvalues of a symmetric tensor and its application to spectral hypergraph theory
- A sequential subspace projection method for extreme Z-eigenvalues of supersymmetric tensors
- Shifted Power Method for Computing Tensor Eigenpairs
- Global Convergence Properties of Conjugate Gradient Methods for Optimization
- On the Best Rank-1 and Rank-(R1 ,R2 ,. . .,RN) Approximation of Higher-Order Tensors
- The Fiedler Vector of a Laplacian Tensor for Hypergraph Partitioning
- A Nonlinear Conjugate Gradient Method with a Strong Global Convergence Property
- Hypergraph Clustering Using a New Laplacian Tensor with Applications in Image Processing
- A convergent Newton algorithm for computing Z-eigenvalues of an almost nonnegative irreducible tensor
- An Adaptive Shifted Power Method for Computing Generalized Tensor Eigenpairs
- All Real Eigenvalues of Symmetric Tensors
- A New Conjugate Gradient Method with Guaranteed Descent and an Efficient Line Search
- Function minimization by conjugate gradients
- The conjugate gradient method in extremal problems
- Methods of conjugate gradients for solving linear systems
- New properties of a nonlinear conjugate gradient method
This page was built for publication: A family of gradient methods using Householder transformation with application to hypergraph partitioning
