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We consider the symmetric Toeplitz matrix completion problem, whose matrix under consideration possesses specific row and column structures. This problem, which has wide application in diverse areas, is well-known to be computationally…

Optimization and Control · Mathematics 2024-03-15 Xihong Yan , Jiahao Guo , Yi Xu

This paper considers the matrix completion problem. We show that it is not necessary to assume joint incoherence, which is a standard but unintuitive and restrictive condition that is imposed by previous studies. This leads to a sample…

Information Theory · Computer Science 2016-11-15 Yudong Chen

In this paper, we present a unified analysis of matrix completion under general low-dimensional structural constraints induced by {\em any} norm regularization. We consider two estimators for the general problem of structured matrix…

Machine Learning · Statistics 2018-11-26 Suriya Gunasekar , Arindam Banerjee , Joydeep Ghosh

We consider the one-dimensional nonlinear Schr\"odinger equation $$ iu_t + u_{xx} + \mathcal{N}(u)u=0, \quad x,t \in \mathbb R, $$ with the nonlinearity term that is expressed as a sum of powers, possibly infinite: $$ \mathcal{N}(u) = \sum…

Analysis of PDEs · Mathematics 2026-02-19 Oscar Riaño , Alex D Rodriguez , Svetlana Roudenko

The Schur decomposition of a square matrix $A$ is an important intermediate step of state-of-the-art numerical algorithms for addressing eigenvalue problems, matrix functions, and matrix equations. This work is concerned with the following…

Numerical Analysis · Mathematics 2022-03-22 Zvonimir Bujanović , Daniel Kressner , Christian Schröder

We consider the problem of efficiently solving large-scale linear least squares problems that have one or more linear constraints that must be satisfied exactly. Whilst some classical approaches are theoretically well founded, they can face…

Numerical Analysis · Mathematics 2021-12-24 Jennifer Scott , Miroslav Tuma

We establish a relationship between an inverse optimization spectral problem for N-dimensional Schr\"odinger equation $ -\Delta \psi+q\psi=\lambda \psi $ and a solution of the nonlinear boundary value problem $-\Delta u+q_0 u=\lambda u-…

Analysis of PDEs · Mathematics 2018-03-06 Y. Sh. Ilyasov , N. F. Valeev

We present the first parallel algorithm for solving systems of linear equations in symmetric, diagonally dominant (SDD) matrices that runs in polylogarithmic time and nearly-linear work. The heart of our algorithm is a construction of a…

Numerical Analysis · Computer Science 2013-11-14 Richard Peng , Daniel A. Spielman

We systematically introduce an approach to the analysis and (numerical) solution of a broad class of nonlinear unconstrained optimal control problems, involving ordinary and distributed systems. Our approach relies on exact representations…

Optimization and Control · Mathematics 2025-02-04 Nikolay Pogodaev , Maxim Staritsyn

The problem of computing spectra of operators is arguably one of the most investigated areas of computational mathematics. However, the problem of computing spectra of general bounded infinite matrices has only recently been solved. We…

Spectral Theory · Mathematics 2022-09-20 Matthew J. Colbrook , Anders C. Hansen

A system of semi-discrete coupled nonlinear Schr\"{o}dinger equations is studied. To show the complete integrability of the model with multiple components, we extend the discrete version of the inverse scattering method for the…

solv-int · Physics 2007-05-23 T. Tsuchida , H. Ujino , M. Wadati

We solve inverse scattering problem for Schr\"odinger operators with compactly supported potentials on the half line. We discretize S-matrix: we take the value of the S-matrix on some infinite sequence of positive real numbers. Using this…

Mathematical Physics · Physics 2020-10-08 Evgeny L. Korotyaev

In this paper, we introduce a novel and robust approach to Quantized Matrix Completion (QMC). First, we propose a rank minimization problem with constraints induced by quantization bounds. Next, we form an unconstrained optimization problem…

Machine Learning · Statistics 2019-02-20 Ashkan Esmaeili , Farokh Marvasti

Semidefinite programming (SDP) is a unifying framework that generalizes both linear programming and quadratically-constrained quadratic programming, while also yielding efficient solvers, both in theory and in practice. However, there exist…

Data Structures and Algorithms · Computer Science 2022-10-24 Elena Grigorescu , Young-San Lin , Sandeep Silwal , Maoyuan Song , Samson Zhou

Pairwise comparison matrices are increasingly used in settings where some pairs are missing. However, there exist few inconsistency indices for similar incomplete data sets and no reasonable measure has an associated threshold. This paper…

Statistics Theory · Mathematics 2022-02-03 Kolos Csaba Ágoston , László Csató

We compare the distribution function and the maximum of solutions of nonlinear elliptic equations defined in general domains with solutions of similar problems defined in a ball using Schwarz symmetrization. As an application, we prove the…

Analysis of PDEs · Mathematics 2021-07-02 Leonardo Prange Bonorino , José Fábio Bezerra Montenegro

We propose a new formulation for the bundle adjustment problem which relies on nullspace marginalization of landmark variables by QR decomposition. Our approach, which we call square root bundle adjustment, is algebraically equivalent to…

Computer Vision and Pattern Recognition · Computer Science 2021-11-23 Nikolaus Demmel , Christiane Sommer , Daniel Cremers , Vladyslav Usenko

Let $\mathcal{M}$ be a square matrix over a commutative ring and let $\mathcal{A}$ be a principal submatrix. We give relations between the determinants of $\mathcal{M}$ and $\mathcal{A}$ based on an annihilating polynomial for one of them.…

Rings and Algebras · Mathematics 2017-03-08 M. Thüne

In this paper, we first introduce R0-W and SSM-W properties for the set of matrices which is a generalization of R0 and the strictly semimonotone matrix. We then prove some existence results for the extended horizontal linear…

Optimization and Control · Mathematics 2023-01-05 Punit Kumar Yadav , K. Palpandi

We study the spectral properties of infinitely smooth multivariate kernel matrices when the nodes form a single cluster. We show that the geometry of the nodes plays an important role in the scaling of the eigenvalues of these kernel…

Numerical Analysis · Mathematics 2026-01-12 Nuha Diab , Dmitry Batenkov
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