Adaptively sketched Bregman projection methods for linear systems
From MaRDI portal
Publication:5076003
DOI10.1088/1361-6420/ac5f76OpenAlexW4220933353MaRDI QIDQ5076003
Lu Zhang, Hong-Xia Wang, Ziyang Yuan, Hui Zhang
Publication date: 12 May 2022
Published in: Inverse Problems (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2112.14456
Related Items (2)
Randomized Douglas–Rachford Methods for Linear Systems: Improved Accuracy and Efficiency ⋮ A weighted randomized sparse Kaczmarz method for solving linear systems
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Greedy and randomized versions of the multiplicative Schwarz method
- On Kaczmarz's projection iteration as a direct solver for linear least squares problems
- A randomized Kaczmarz algorithm with exponential convergence
- On relaxed greedy randomized Kaczmarz methods for solving large sparse linear systems
- Linear convergence of the randomized sparse Kaczmarz method
- AIR tools II: algebraic iterative reconstruction methods, improved implementation
- Paved with good intentions: analysis of a randomized block Kaczmarz method
- Linear Convergence of Descent Methods for the Unconstrained Minimization of Restricted Strongly Convex Functions
- Randomized Methods for Linear Constraints: Convergence Rates and Conditioning
- An accelerated randomized Kaczmarz algorithm
- Randomized Iterative Methods for Linear Systems
- On Greedy Randomized Kaczmarz Method for Solving Large Sparse Linear Systems
- On Adaptive Sketch-and-Project for Solving Linear Systems
- Greed Works: An Improved Analysis of Sampling Kaczmarz--Motzkin
- Stochastic Reformulations of Linear Systems: Algorithms and Convergence Theory
- A projective averaged Kaczmarz iteration for nonlinear ill-posed problems
- A new Kaczmarz-type method and its acceleration for nonlinear ill-posed problems
- Convex analysis and monotone operator theory in Hilbert spaces
- Sparse sampling Kaczmarz–Motzkin method with linear convergence
This page was built for publication: Adaptively sketched Bregman projection methods for linear systems