On the generally randomized extended Gauss-Seidel method
From MaRDI portal
Publication:2058411
DOI10.1016/j.apnum.2021.10.018zbMath1484.65064OpenAlexW3209067503WikidataQ114208174 ScholiaQ114208174MaRDI QIDQ2058411
Publication date: 9 December 2021
Published in: Applied Numerical Mathematics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.apnum.2021.10.018
Related Items
On adaptive block coordinate descent methods for ridge regression ⋮ Solving the system of nonsingular tensor equations via randomized Kaczmarz-like method
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- A random coordinate descent algorithm for optimization problems with composite objective function and linear coupled constraints
- Randomized block Kaczmarz method with projection for solving least squares
- Acceleration of randomized Kaczmarz method via the Johnson-Lindenstrauss lemma
- Randomized Kaczmarz solver for noisy linear systems
- A randomized Kaczmarz algorithm with exponential convergence
- On convergence rate of the randomized Kaczmarz method
- On relaxed greedy randomized Kaczmarz methods for solving large sparse linear systems
- On the Meany inequality with applications to convergence analysis of several row-action iteration methods
- On partially randomized extended Kaczmarz method for solving large sparse overdetermined inconsistent linear systems
- On certain iterative methods for solving linear systems
- Randomized Extended Kaczmarz for Solving Least Squares
- Randomized Methods for Linear Constraints: Convergence Rates and Conditioning
- Convergence Properties of the Randomized Extended Gauss--Seidel and Kaczmarz Methods
- Randomized Iterative Methods for Linear Systems
- The Probability That a Numerical Analysis Problem is Difficult
- Sparse Optimization Theory and Methods
- Preasymptotic convergence of randomized Kaczmarz method
- On Greedy Randomized Kaczmarz Method for Solving Large Sparse Linear Systems
- Tight upper bounds for the convergence of the randomized extended Kaczmarz and Gauss–Seidel algorithms
- On greedy randomized coordinate descent methods for solving large linear least‐squares problems
- Rows versus Columns: Randomized Kaczmarz or Gauss--Seidel for Ridge Regression
- Convergence Analysis of Inexact Randomized Iterative Methods