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$L^1$ based optimization is widely used in image denoising, machine learning and related applications. One of the main features of such approach is that it naturally provide a sparse structure in the numerical solutions. In this paper, we…

Numerical Analysis · Mathematics 2023-02-13 Weifeng Qiu , Jin Ren , Ke Shi , Yuesheng Xu

We present a novel iterative algorithm for approximating the linear least squares solution with low complexity. After a motivation of the algorithm we discuss the algorithm's properties including its complexity, and we present theoretical…

Data Structures and Algorithms · Computer Science 2016-11-15 Michael Lunglmayr , Christoph Unterrieder , Mario Huemer

The least squares method provides the best-fit curve by minimizing the total squares error. In this work, we provide the modified least squares method based on the fractional orthogonal polynomials that belong to the space $M_{n}^{\lambda}…

Numerical Analysis · Mathematics 2024-05-02 Abhishek Kumar Singh , Mani Mehra , Anatoly A. Alikhanov

We analyze a divergence based first order system least squares method applied to a second order elliptic model problem with homogeneous boundary conditions. We prove optimal convergence in the $L^2(\Omega)$ norm for the scalar variable.…

Numerical Analysis · Mathematics 2024-07-25 Maximilian Bernkopf , Jens Markus Melenk

This paper presents a unified Least-Squares framework for solving nonlinear partial differential equations by recasting the governing system as a residual minimisation problem. A Least-Squares functional is formulated and the corresponding…

Numerical Analysis · Mathematics 2025-11-10 Fleurianne Bertrand , Maximilian Brodbeck , Tim Ricken , Henrik Schneider

In this paper we propose a variant of the linear least squares model allowing practitioners to partition the input features into groups of variables that they require to contribute similarly to the final result. The output allows…

Machine Learning · Computer Science 2024-07-17 Roberto Esposito , Mattia Cerrato , Marco Locatelli

We propose and analyze a discontinuous least squares finite element method for solving the indefinite time-harmonic Maxwell equations. The scheme is based on the $L^2$ norm least squares functional with the weak imposition of the continuity…

Numerical Analysis · Mathematics 2020-07-15 Ruo Li , Qicheng Liu , Fanyi Yang

The convergence analysis for least-squares finite element methods led to various adaptive mesh-refinement strategies: Collective marking algorithms driven by the built-in a posteriori error estimator or an alternative explicit…

Numerical Analysis · Mathematics 2023-09-18 Philipp Bringmann

We study the finite element approximation of linear second-order elliptic partial differential equations in nondivergence form with highly heterogeneous diffusion and drift coefficients. A generalized Cordes condition is imposed to…

Numerical Analysis · Mathematics 2026-04-17 Moritz Hauck , Roland Maier , Timo Sprekeler

We propose a linear algorithm for determining two function parameters by their linear combination. These functions must satisfy the first order differential equations with polynomial coefficients and our parameters are the coefficients of…

Numerical Analysis · Mathematics 2009-01-09 Oleg I. Berngardt , Alexander L. Voronov

We present a variational algorithm for solving the classical inverse Sturm-Liouville problem in one dimension when two spectra are given. All critical points of the least squares functional are at global minima, which which suggests…

Numerical Analysis · Mathematics 2009-11-11 Norbert Roehrl

We introduce a direct numerical treatment of nonlinear higher-index differential-algebraic equations by means of overdetermined polynomial least-squares collocation. The procedure is not much more computationally expensive than standard…

Numerical Analysis · Mathematics 2019-03-22 Michael Hanke , Roswitha März

This article proposes a new numerical algorithm for second order elliptic equations in non-divergence form. The new method is based on a discrete weak Hessian operator locally constructed by following the weak Galerkin strategy. The…

Numerical Analysis · Mathematics 2015-10-14 Chunmei Wang , Junping Wang

We present a two-stage least-squares method to inverse medium problems of reconstructing multiple unknown coefficients simultaneously from noisy data. A direct sampling method is applied to detect the location of the inhomogeneity in the…

Numerical Analysis · Mathematics 2022-01-04 Kazufumi Ito , Ying Liang , Jun Zou

We provide new insights into the a priori theory for a time-stepping scheme based on least-squares finite element methods for parabolic first-order systems. The elliptic part of the problem is of general reaction-convection-diffusion type.…

Numerical Analysis · Mathematics 2018-05-14 Thomas Führer , Michael Karkulik

Various approaches to iterative refinement (IR) for least-squares problems have been proposed in the literature and it may not be clear which approach is suitable for a given problem. We consider three approaches to IR for least-squares…

Numerical Analysis · Mathematics 2025-01-20 Erin Carson , Ieva Daužickaitė

We propose a numerical method to approximate the solution of second order elliptic problems in nonvariational form. The method is of Galerkin type using conforming finite elements and applied directly to the nonvariational (nondivergence)…

Numerical Analysis · Mathematics 2011-05-19 Omar Lakkis , Tristan Pryer

Solving an integer least squares (ILS) problem usually consists of two stages: reduction and search. This thesis is concerned with the reduction process for the ordinary ILS problem and the ellipsoid-constrained ILS problem. For the…

Optimization and Control · Mathematics 2015-03-17 Mazen Al Borno

This paper introduces a nonconforming virtual element method for general second-order elliptic problems with variable coefficients on domains with curved boundaries and curved internal interfaces. We prove arbitrary order optimal…

Numerical Analysis · Mathematics 2024-10-25 Yi Liu , Alessandro Russo

It is shown that the computational efficiency of the discrete least-squares (DLS) approximation of solutions of stochastic elliptic PDEs is improved by incorporating a reduced-basis method into the DLS framework. The goal is to recover the…

Numerical Analysis · Mathematics 2017-11-09 Max Gunzburger , Michael Schneier , Clayton Webster , Guannan Zhang