Apr 21, 2022 · Abstract:This work aims to accelerate the convergence of proximal gradient methods used to solve regularized linear inverse problems.
This work proposes a generalizable polynomial-based preconditioner for faster iterative convergence of regularized linear inverse problems that leverage ...
A polynomial-based preconditioner that targets the eigenvalue spectrum of the normal operator derived from the linear operator that does not assume any ...
Details ; Title. Polynomial Preconditioners for Regularized Linear Inverse Problems ; Is Part Of. SIAM journal on imaging sciences, 2024-03, Vol.17 (1), p.116-146.
This repository reproduces the experiments in Polynomial Preconditioners for Regularized Linear Inverse Problems. Written by Siddharth Srinivasan. Please ...
The preconditioner, implemented as a helical polynomial division, uses dips estimated from plane-wave destruction (Fomel, 2002) to determine the appropriate ...
Abstract. Preconditioning techniques for linear systems are widely used in order to speed up the convergence of iterative methods. If the linear system is ...
Polynomial preconditioners can be considered as members of the second class of preconditioners: direct approximations of the inverse of the coefficient matrix.
Missing: Regularized | Show results with:Regularized
We consider preconditioned regularized Newton methods tailored to the efficient solution of nonlinear large-scale exponentially ill-posed problems.
The goal of this lecture is to provide an overview of important techniques used for the anal- ysis, regularization, and numerical solution of inverse ...