Cover Image

Split Bregman Isotropic and Anisotropic Image Deblurring with Kronecker Product Sum Approximations using Single Precision Enlarged-GKB or RSVD Algorithms to provide low rank truncated SVDs

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Alsubhi, Abdulmajeed, Renaut, Rosemary
Format:	Preprint
Published:	2024
Subjects:	Numerical Analysis 65F22, 65F10, 68W40
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Efficient Decomposition-Based Algorithms for $\ell_1$-Regularized Inverse Problems with Column-Orthogonal and Kronecker Product Matrices
by: Sweeney, Brian, et al.
Published: (2024)

Parameter Selection by GCV and a $χ^2$ test within Iterative Methods for $\ell_1$-regularized Inverse Problems
by: Sweeney, Brian, et al.
Published: (2024)

Algorithm-agnostic low-rank approximation of operator monotone matrix functions
by: Persson, David, et al.
Published: (2023)

Sketched and truncated polynomial Krylov methods: Evaluation of matrix functions
by: Palitta, Davide, et al.
Published: (2023)

Randomized block-Krylov subspace methods for low-rank approximation of matrix functions
by: Persson, David, et al.
Published: (2025)

Variable Projection Methods for Solving Regularized Separable Inverse Problems with Applications to Semi-Blind Image Deblurring
by: Salzer, Delfina B. Comerso, et al.
Published: (2026)

Sharp analysis of sketched least squares and randomized low-rank approximation
by: Epperly, Ethan N., et al.
Published: (2026)

Beyond Low Rank: Fast Low-Rank + Diagonal Decomposition with a Spectral Approach
by: Yeon, Kingsley, et al.
Published: (2025)

Subspace-constrained randomized coordinate descent for linear systems with good low-rank matrix approximations
by: Lok, Jackie, et al.
Published: (2025)

Fast randomized numerical rank estimation for numerically low-rank matrices
by: Meier, Maike, et al.
Published: (2021)

Preconditioning via Randomized Range Deflation (RandRAND)
by: Balabanov, Oleg, et al.
Published: (2025)

Randomized low-rank Runge-Kutta methods
by: Lam, Hei Yin, et al.
Published: (2024)

Improving Sketching Algorithms for Low-Rank Matrix Approximation via Sketch-Power Iterations
by: Chang, Chao, et al.
Published: (2026)

Randomized Large-Scale Quaternion Matrix Approximation: Practical Rangefinders and One-Pass Algorithm
by: Chang, Chao, et al.
Published: (2024)

GMRES with randomized sketching and deflated restarting
by: Burke, Liam, et al.
Published: (2023)

Sketched and Truncated Polynomial Krylov Subspace Methods: Matrix Sylvester Equations
by: Palitta, Davide, et al.
Published: (2023)

Fast $\ell_1$-Regularized EEG Source Localization Using Variable Projection
by: Solomon, Jack Michael, et al.
Published: (2025)

Numerical Instabilities in the Kaczmarz Method and Stabilization by Iterative Refinement
by: Dereziński, Michał, et al.
Published: (2026)

Randomized methods for dynamical low-rank approximation
by: Carrel, Benjamin
Published: (2024)

Adaptive randomized pivoting for column subset selection, DEIM, and low-rank approximation
by: Cortinovis, Alice, et al.
Published: (2024)

On a randomized small-block Lanczos method for large-scale null space computations
by: Kressner, Daniel, et al.
Published: (2024)

Convergence Analysis of a Variable Projection Method for Regularized Separable Nonlinear Inverse Problems
by: Español, Malena I., et al.
Published: (2024)

The Detection and Correction of Silent Errors in Pipelined Krylov Subspace Methods
by: Carson, Erin Claire, et al.
Published: (2024)

Relaxed Greedy Randomized Kaczmarz with Signal Averaging for Solving Doubly-Noisy Linear Systems
by: Zhang, Lu, et al.
Published: (2026)

Randomized flexible Krylov methods for $\ell_p$ regularization
by: Landman, Malena Sabaté, et al.
Published: (2025)

Detecting when one probe vector is enough for preconditioned log-determinant approximation
by: Cortinovis, Alice, et al.
Published: (2026)

Accelerating a restarted Krylov method for matrix functions with randomization
by: Guidotti, Nicolas L., et al.
Published: (2025)

A general framework for Krylov ODE residuals with applications to randomized Krylov methods
by: Krieger, Emil, et al.
Published: (2025)

Fast and forward stable randomized algorithms for linear least-squares problems
by: Epperly, Ethan N.
Published: (2023)

Fast randomized least-squares solvers can be just as accurate and stable as classical direct solvers
by: Epperly, Ethan N., et al.
Published: (2024)

Two Variations on the XTrace Algorithm
by: Hallman, Eric
Published: (2025)

A class of low-rank short recurrences for nonsymmetric linear matrix equations
by: Palitta, Davide, et al.
Published: (2026)

Make the most of what you have: Resource-efficient randomized algorithms for matrix computations
by: Epperly, Ethan N.
Published: (2025)

Acceleration and restart for the randomized Bregman-Kaczmarz method
by: Tondji, Lionel, et al.
Published: (2023)

Convergence analysis of online algorithms for vector-valued kernel regression
by: Griebel, Michael, et al.
Published: (2023)

Sequential Least-Squares Estimators with Fast Randomized Sketching for Linear Statistical Models
by: Chen, Guan-Yu, et al.
Published: (2025)

Robust, randomized preconditioning for kernel ridge regression
by: Díaz, Mateo, et al.
Published: (2023)

Recursive sparse LU decomposition based on nested dissection and low rank approximations
by: Xuanru, Zhu, et al.
Published: (2024)

FlexTrace: Exchangeable Randomized Trace Estimation for Matrix Functions
by: Madhavan, Madhusudan, et al.
Published: (2026)

Riemannian multigrid line search for low-rank problems
by: Sutti, Marco, et al.
Published: (2020)