The Stacked Linear Algebra Graph implements a directed graph with a weight on each vertex and edge. The graph models vertices and adjacency matrices as GraphBLAS sparse vectors and matrices ...

Abstract: In this paper we consider some problems of graph theory from the linear algebra point of view. It turns out, that this approach allows us to prove certain theorems on minimum edge coverings ...

A project headed by the SEI’s Scott McMillan took a step in 2020 toward standardizing graph algorithm application development in C++. The GraphBLAS, Basic Linear Algebra Subprograms for Graphs, is a ...

Abstract: In this paper, we consider some known problems of graph theory from the linear algebra point of view. Studying features of vector spaces over characteristic-two finite field allows us to ...

Graph algorithms can be expressed as sequences of linear, algebra-like operations through the use of the adjacency matrix. Adjacency matrices are used to represent graphs instead of vertices and edges ...

Spectral clustering is an unsupervised learning technique that identifies clusters in data by analyzing the eigenstructure of a similarity matrix. Unlike traditional clustering algorithms that use ...

ABSTRACT: Let G be a graph and A=(aij)n×n be the adjacency matrix of G, the eigenvalues of A are said to be the eigenvalues of the graph G, and to form the spectrum of this graph. The numbers of ...

Vector set of graphs or charts with 12 basic mathematical functions with grid and coordinates. Linear, constant, absolute value, greatest integer, logarithmic, exponential, reciprocal, square root, ...

Vector set of graphs or charts with 12 basic mathematical functions with grid and coordinates. Linear, constant, absolute value, greatest integer, logarithmic, exponential, reciprocal, square root, ...