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An expression for the Moore-Penrose inverse of a matrix of the form M = XNY , where X and Y are nonsingular, has been recently established by Castro-Gonz\'alez et al. [1, Theorem 2.2]. The expression plays an essential role in developing…

Numerical Analysis · Mathematics 2016-12-06 Xuefeng Xu

We present a method for estimating sparse high-dimensional inverse covariance and partial correlation matrices, which exploits the connection between the inverse covariance matrix and linear regression. The method is a two-stage estimation…

Machine Learning · Statistics 2025-05-13 Samuel Erickson , Tobias Rydén

Due to the high computational load of modern numerical simulation, there is a demand for approaches that would reduce the size of discrete problems while keeping the accuracy reasonable. In this work, we present an original algorithm to…

Machine Learning · Computer Science 2025-07-25 Sergei Shumilin , Alexander Ryabov , Nikolay Yavich , Evgeny Burnaev , Vladimir Vanovskiy

In this paper we present two different variants of method for symmetric matrix inversion, based on modified Gaussian elimination. Both methods avoid computation of square roots and have a reduced machine time's spending. Further, both of…

Mathematical Software · Computer Science 2015-04-28 Anton Kochnev , Nicolai Savelov

The problem of polynomial least squares fitting in the standard Lagrange basis is addressed in this work. Although the matrices involved in the corresponding overdetermined linear systems are not totally positive, rectangular totally…

Numerical Analysis · Mathematics 2023-09-25 Ana Marco , José-Javier Martínez , Raquel Viaña

In this paper, we propose a unified convergence analysis for a class of generic shuffling-type gradient methods for solving finite-sum optimization problems. Our analysis works with any sampling without replacement strategy and covers many…

Optimization and Control · Mathematics 2021-09-21 Lam M. Nguyen , Quoc Tran-Dinh , Dzung T. Phan , Phuong Ha Nguyen , Marten van Dijk

The solution of parameter-dependent linear systems, by classical methods, leads to an arithmetic effort that grows exponentially in the number of parameters. This renders the multigrid method, which has a well understood convergence theory,…

Numerical Analysis · Mathematics 2020-08-04 Lars Grasedyck , Maren Klever , Christian Löbbert , Tim A. Werthmann

The aim of this work is to characterize linear maps of inner pro\-duct infinite-dimensional vector spaces where the Moore-Penrose inverse exists. This MP inverse generalizes the well-known Moore-Penrose inverse of a matrix $A\in…

Rings and Algebras · Mathematics 2020-07-07 V. Cabezas Sánchez , F. Pablos Romo

This paper is devoted to studying the global and finite convergence of the semi-smooth Newton method for solving a piecewise linear system that arises in cone-constrained quadratic programming problems and absolute value equations. We first…

Optimization and Control · Mathematics 2023-01-24 Nicolas F. Armijo , Yunier Bello-Cruz , Gabriel Haeser

This work is devoted to the study of the symmetries of (quasi)periodic architectured materials. For this purpose, the weaker symmetry criterion of indistinguishability is used. It relies on a statistical description of the mesostructure and…

Mathematical Physics · Physics 2026-04-03 Markus Hubert , Christelle Combescure , Renald Brenner , Nicolas Auffray

We introduce a framework for quasi-Newton forward--backward splitting algorithms (proximal quasi-Newton methods) with a metric induced by diagonal $\pm$ rank-$r$ symmetric positive definite matrices. This special type of metric allows for a…

Optimization and Control · Mathematics 2018-11-27 Stephen Becker , Jalal Fadili , Peter Ochs

A new integration technique for multi-loop Feynman integrals, called the matrix method, is developed and then applied to the divergent part of the overlapping two-loop quark self-energy function $\,i\Sigma\,$ in the light- cone gauge. It is…

High Energy Physics - Theory · Physics 2009-10-28 George Leibbrandt , Jimmy Williams

FOCal Underdetermined System Solver (FOCUSS) is a powerful tool for sparse representation and underdetermined inverse problems, which is extremely easy to implement. In this paper, we give a comprehensive convergence analysis on the FOCUSS…

Information Theory · Computer Science 2013-04-19 Zhaoshui He , Shengli Xie , Andrzej Cichocki

This paper presents an improved forward-backward splitting algorithm with two inertial parameters. It aims to find a point in the real Hilbert space at which the sum of a co-coercive operator and a maximal monotone operator vanishes. Under…

Machine Learning · Computer Science 2025-05-08 İrfan Işik , Ibrahim Karahan , Okan Erkaymaz

We develop a novel, fundamental and surprisingly simple randomized iterative method for solving consistent linear systems. Our method has six different but equivalent interpretations: sketch-and-project, constrain-and-approximate, random…

Numerical Analysis · Mathematics 2016-01-07 Robert M. Gower , Peter Richtárik

The goal of this primer is to provide a relatively short exposition of the basics of multigrid methods, simplified by focusing on fundamental concepts in a variational setting. This is done by way of a quadratic energy minimization…

Numerical Analysis · Mathematics 2026-05-19 Stephen F. McCormick , Rasmus Tamstorf

We reconsider the mass spectrum of double sine-Gordon theory where recent semiclassical results called into question the previously accepted picture. We use the Truncated Conformal Space Approach (TCSA) to investigate the claims. We…

High Energy Physics - Theory · Physics 2008-11-26 G. Takacs , F. Wagner

In this paper, we describe an algorithm for computing the left, right, or 2-sided congruences of a finitely presented semigroup or monoid with finitely many classes, and an alternative algorithm when the finitely presented semigroup or…

Rings and Algebras · Mathematics 2025-06-26 Marina Anagnostopoulou-Merkouri , Reinis Cirpons , James D. Mitchell , Maria Tsalakou

We develop a framework for quantitative convergence analysis of Picard iterations of expansive set-valued fixed point mappings. There are two key components of the analysis. The first is a natural generalization of single-valued averaged…

Optimization and Control · Mathematics 2018-09-24 D. Russell Luke , Nguyen H. Thao , Matthew K. Tam

We propose a structure of a semiparametric two-component mixture model when one component is parametric and the other is defined through linear constraints on its distribution function. Estimation of a two-component mixture model with an…

Methodology · Statistics 2017-12-22 Diaa Al Mohamad , Assia Boumahdaf
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