The global convergence of the nonlinear power method for mixed-subordinate matrix norms
From MaRDI portal
Publication:2049097
DOI10.1007/s10915-021-01524-wzbMath1473.65047OpenAlexW3171992686MaRDI QIDQ2049097
Matthias Hein, Francesco Tudisco, Gautier, Antoine
Publication date: 24 August 2021
Published in: Journal of Scientific Computing (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s10915-021-01524-w
Fixed-point theorems (47H10) Contraction-type mappings, nonexpansive mappings, (A)-proper mappings, etc. (47H09) Positive matrices and their generalizations; cones of matrices (15B48) Numerical computation of matrix norms, conditioning, scaling (65F35)
Related Items (3)
A new centrality measure based on random walks for multilayer networks under the framework of tensor computation ⋮ Nonlinear Perron--Frobenius Theorems for Nonnegative Tensors ⋮ Node and Layer Eigenvector Centralities for Multiplex Networks
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Tensor norm and maximal singular vectors of nonnegative tensors -- a Perron-Frobenius theorem, a Collatz-Wielandt characterization and a generalized power method
- Monotonicity properties of norms
- Estimating the matrix \(p\)-norm
- The restricted isometry property and its implications for compressed sensing
- Functional analysis, Sobolev spaces and partial differential equations
- Convergence of a subgradient method for computing the bound norm of matrices
- The power method for l\(^p\) norms
- Finsler structures for the part metric and Hilbert's projective metric and applications to ordinary differential equations
- Perron-Frobenius theorem for nonnegative multilinear forms and extensions
- On complex power nonnegative matrices
- Grothendieck constant is norm of Strassen matrix multiplication tensor
- Non-negative matrices and Markov chains.
- Estimating the Largest Elements of a Matrix
- The Computational Complexity of Duality
- Nonlinear Perron–Frobenius Theory
- Grothendieck-Type Inequalities in Combinatorial Optimization
- Restricted Isometry Property for General p-Norms
- Matrix p-Norms Are NP-Hard to Approximate If $p\neq1,2,\infty$
- Computing the norm ∥A∥∞,1 is NP-hard∗
- Regularized learning schemes in feature Banach spaces
- An elementary proof of the Birkhoff-Hopf theorem
- Experience with a Matrix Norm Estimator
- Accuracy and Stability of Numerical Algorithms
- The Perron--Frobenius Theorem for Multihomogeneous Mappings
- A Unifying Perron--Frobenius Theorem for Nonnegative Tensors via Multihomogeneous Maps
- The contractivity of cone-preserving multilinear mappings
- Hypercontractivity, sum-of-squares proofs, and their applications
- An Introduction to Metric Spaces and Fixed Point Theory
This page was built for publication: The global convergence of the nonlinear power method for mixed-subordinate matrix norms
