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The theory of matrix splitting is a useful tool for finding solution of rectangular linear system of equations, iteratively. The purpose of this paper is two-fold. Firstly, we revisit theory of weak regular splittings for rectangular…

Numerical Analysis · Mathematics 2016-08-23 Debasisha Mishra

This paper presents a probabilistic perspective on iterative methods for approximating the solution $\mathbf{x}_* \in \mathbb{R}^d$ of a nonsingular linear system $\mathbf{A} \mathbf{x}_* = \mathbf{b}$. In the approach a standard iterative…

Methodology · Statistics 2021-01-12 Jon Cockayne , Ilse C. F. Ipsen , Chris J. Oates , Tim W. Reid

In this paper, we introduce and study a new extragradient iterative process for finding a common element of the set of fixed points of an infinite family of nonexpansive mappings and the set of solutions of a variational inequality for an…

Functional Analysis · Mathematics 2014-05-22 Ibrahim Karahan , Murat Ozdemir

We investigate the iterative methods proposed by Maz'ya and Kozlov (see [KM1], [KM2]) for solving ill-posed inverse problems modeled by partial differential equations. We consider linear evolutionary problems of elliptic, hyperbolic and…

Numerical Analysis · Mathematics 2020-12-01 J. Baumeister , A. Leitao

In this paper we propose a new class of iterative regularization methods for solving ill-posed linear operator equations. The prototype of these iterative regularization methods is in the form of second order evolution equation with a…

Numerical Analysis · Mathematics 2020-06-24 Rongfang Gong , B. Hofmann , Ye Zhang

We consider perturbed nonlinear ill-posed equations in Hilbert spaces, with operators that are monotone on a given closed convex subset. A simple stable approach is Lavrentiev regularization, but existence of solutions of the regularized…

Numerical Analysis · Mathematics 2018-06-05 Robert Plato , Bernd Hofmann

This work aims at solving the problems with intractable sparsity-inducing norms that are often encountered in various machine learning tasks, such as multi-task learning, subspace clustering, feature selection, robust principal component…

Machine Learning · Computer Science 2019-07-03 Feiping Nie , Zhanxuan Hu , Xiaoqian Wang , Rong Wang , Xuelong Li , Heng Huang

In this paper, we first propose a new Levenberg-Marquardt method for solving constrained (and not necessarily square) nonlinear systems. Basically, the method combines the unconstrained Levenberg-Marquardt method with a type of feasible…

Optimization and Control · Mathematics 2019-08-20 Douglas S. Gonçalves , Max L. N. Gonçalves , Fabrícia R. Oliveira

In this manuscript we propose and analyze an implicit two-point type method (or inertial method) for obtaining stable approximate solutions to linear ill-posed operator equations. The method is based on the iterated Tikhonov (iT) scheme. We…

Numerical Analysis · Mathematics 2024-01-30 Joel C. Rabelo , Antonio Leitão , Alexandre L. Madureira

A multiscale numerical method is proposed for the solution of semi-linear elliptic stochastic partial differential equations with localized uncertainties and non-linearities, the uncertainties being modeled by a set of random parameters. It…

Numerical Analysis · Mathematics 2019-01-23 Anthony Nouy , Florent Pled

We investigate a level-set type method for solving ill-posed problems, with the assumption that the solutions are piecewise, but not necessarily constant functions with unknown level sets and unknown level values. In order to get stable…

Numerical Analysis · Mathematics 2012-10-30 Adriano De Cezaro

Various versions of the Dynamical Systems Method (DSM) are proposed for solving linear ill-posed problems with bounded and unbounded operators. Convergence of the proposed methods is proved. Some new results concerning discrepancy principle…

Numerical Analysis · Mathematics 2007-05-23 A. G. Ramm

We present the first framework to solve linear inverse problems leveraging pre-trained latent diffusion models. Previously proposed algorithms (such as DPS and DDRM) only apply to pixel-space diffusion models. We theoretically analyze our…

Machine Learning · Computer Science 2023-07-04 Litu Rout , Negin Raoof , Giannis Daras , Constantine Caramanis , Alexandros G. Dimakis , Sanjay Shakkottai

Choosing an appropriate regularization term is necessary to obtain a meaningful solution to an ill-posed linear inverse problem contaminated with measurement errors or noise. The $\ell_p$ norm covers a wide range of choices for the…

Numerical Analysis · Mathematics 2020-12-30 Jeffrey Cornelis , Wim Vanroose

We propose a new approach to linear ill-posed inverse problems. Our algorithm alternates between enforcing two constraints: the measurements and the statistical correlation structure in some transformed space. We use a non-linear multiscale…

Computational Engineering, Finance, and Science · Computer Science 2018-12-04 Ivan Dokmanić , Joan Bruna , Stéphane Mallat , Maarten de Hoop

We propose a new fast algorithm for solving one of the standard approaches to ill-posed linear inverse problems (IPLIP), where a (possibly non-smooth) regularizer is minimized under the constraint that the solution explains the observations…

Optimization and Control · Mathematics 2012-10-10 Manya V. Afonso , José M. Bioucas-Dias , Mário A. T. Figueiredo

We consider algebraic iterative reconstruction methods with applications in image reconstruction. In particular, we are concerned with methods based on an unmatched projector/backprojector pair; i.e., the backprojector is not the exact…

Numerical Analysis · Mathematics 2019-02-14 Yiqiu Dong , Per Christian Hansen , Michiel E. Hochstenbach , Nicolai Andre Brogaard Riis

We consider a regularization concept for the solution of ill--posed operator equations, where the operator is composed of a continuous and a discontinuous operator. A particular application is level set regularization, where we develop a…

Numerical Analysis · Mathematics 2020-11-16 F. Frühauf , O. Scherzer , A. Leitao

This paper deals with a modifed iterative projection method for approximating a solution of hierarchical fixed point problems for nearly nonexpansive mappings. Some strong convergence theorems for the proposed method are presented under…

Functional Analysis · Mathematics 2014-03-17 Ibrahim Karahan , Murat Ozdemir

A simple iteration methodology for the solution of a set of a linear algebraic equations is presented. The explanation of this method is based on a pure geometrical interpretation and pictorial representation. Convergence using this method…

Computational Physics · Physics 2010-12-30 Avas V. Khugaev , Renat A. Sultanov , D. Guster
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