Evaluating an extremely useful graph property, the spectral radius (largest absolute
eigenvalue of the graph adjacency matrix), for large graphs requires excessive computing …

The spectral radius of a graph, ie, the largest eigenvalue of its adjacency matrix, is of high
interest in graph analytics for Big Data due to its relevance to many important properties of …

Extremely large graphs, such as those representing the Web or online social networks,
require prohibitively large computational resources for an analysis of any of their complex …

Graphs are naturally associated with matrices, as matrices provide a simple way of
representing graphs in computer memory. The basic one of these is the adjacency matrix …

The spectrum of a network or graph G=(V,E) with adjacency matrix A, consists of the
eigenvalues of the normalized Laplacian L=ID^-1/2AD^-1/2. This set of eigenvalues …

The spectral radius of a directed graph is a metric that can only be computed when the
structure of the network is completely known. However, in many practical scenarios, it is not …

The spectral radius of a network graph is the largest Eigen value of the adjacency matrix of
the graph. We hypothesize the spectral radius to be a measure of the variation in the …

Spectral graph theory is the study of the eigenvalues and eigenvectors of matrices
associated with graphs. In this tutorial, we will try to provide some intuition as to why these …

Graphs are the cornerstone of many algorithms pertaining to various network analyses.
When the problem's dimensionality is relatively small, expressed in the number of vertices …

The spectral radius of a graph (ie, the largest eigenvalue of its corresponding adjacency
matrix) plays an important role in modeling virus propagation in networks. In fact, the smaller …