Results 11 to 20 of about 107,141 (312)

Nodal decompositions of a symmetric matrix [PDF]

open access: greenInternational Mathematics Research Notices, 2023
Abstract Analyzing nodal domains is a way to discern the structure of eigenvectors of operators on a graph. We give a new definition extending the concept of nodal domains to arbitrary signed graphs, and therefore to arbitrary symmetric matrices.
Theo McKenzie, John Urschel
openalex   +3 more sources

Symmetric nonnegative matrix trifactorization

open access: yesLinear Algebra and its Applications, 2023
The Symmetric Nonnegative Matrix Trifactorization (SN-Trifactorization) is a factorization of an $n \times n$ nonnegative symmetric matrix $A$ of the form $BCB^T$, where $C$ is a $k \times k$ symmetric matrix, and both $B$ and $C$ are required to be nonnegative.
Damjana Kokol Bukovšek, Helena Šmigoc
openaire   +2 more sources

Matrix polynomials orthogonal with respect to a non-symmetric matrix of measures [PDF]

open access: yesOpuscula Mathematica, 2016
The paper focuses on matrix-valued polynomials satisfying a three-term recurrence relation with constant matrix coefficients. It is shown that they form an orthogonal system with respect to a matrix of measures, not necessarily symmetric. Moreover, it is
Marcin J. Zygmunt
doaj   +1 more source

Symmetric Linearizations for Matrix Polynomials [PDF]

open access: yesSIAM Journal on Matrix Analysis and Applications, 2007
The aim of this paper is to gain new insight into the vector spaces of pencils \({\mathbf L}_1(P)\) and \({\mathbf L}_2(P)\), and their intersection \(\text{DL}(P)\), that arise in connection with the linearization of the polynomial eigenvalue problem \(P(\lambda)x = 0\).
Higham, Nicholas J.   +3 more
openaire   +1 more source

Self-Supervised Symmetric Nonnegative Matrix Factorization [PDF]

open access: yesIEEE Transactions on Circuits and Systems for Video Technology, 2022
Symmetric nonnegative matrix factorization (SNMF) has demonstrated to be a powerful method for data clustering. However, SNMF is mathematically formulated as a non-convex optimization problem, making it sensitive to the initialization of variables. Inspired by ensemble clustering that aims to seek a better clustering result from a set of clustering ...
Yuheng Jia   +4 more
openaire   +2 more sources

Noncommutative symmetric functions with matrix parameters [PDF]

open access: yesDiscrete Mathematics & Theoretical Computer Science, 2012
We define new families of noncommutative symmetric functions and quasi-symmetric functions depending on two matrices of parameters, and more generally on parameters associated with paths in a binary tree. Appropriate specializations of both matrices then
Alain Lascoux   +2 more
doaj   +1 more source

Generalized matrix functions, determinant and permanent

open access: yesپژوهش‌های ریاضی, 2022
Introduction Since linear and multilinear algebra has many applications in different branches of sciences, the attention of many mathematicians has been attracted to it in recent decades. The determinant and the permanent are the most important functions
Mohammad Hossein Jafari, Ali Reza Madadi
doaj  

Off-diagonal symmetric nonnegative matrix factorization [PDF]

open access: yesNumerical Algorithms, 2021
Symmetric nonnegative matrix factorization (symNMF) is a variant of nonnegative matrix factorization (NMF) that allows to handle symmetric input matrices and has been shown to be particularly well suited for clustering tasks. In this paper, we present a new model, dubbed off-diagonal symNMF (ODsymNMF), that does not take into account the diagonal ...
François Moutier   +2 more
openaire   +3 more sources

A recursive condition for the symmetric nonnegative inverse eigenvalue problem

open access: yesRevista Integración, 2017
In this paper we present a sufficient ondition and a necessary condition for Symmetri Nonnegative Inverse Eigenvalue Problem. This condition is independent of the existing realizability criteria.
Elvis Ronald Valero   +2 more
doaj   +1 more source

Unfolding a symmetric matrix [PDF]

open access: yesJournal of Classification, 1996
Graphical displays which show inter--sample distances are important for the interpretation and presentation of multivariate data. Except when the displays are two--dimensional, however, they are often difficult to visualize as a whole. A device, based on multidimensional unfolding, is described for presenting some intrinsically high-
John C. Gower, Michael Greenacre
openaire   +3 more sources

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