Recently, hardness results for problems in P were achieved using reasonable complexity-
theoretic assumptions such as the Strong Exponential Time Hypothesis. According to these …

We present new algorithms for finding induced four-node subgraphs in a given graph, which
run in time roughly that of detecting a clique on three nodes (ie, a triangle). The best known …

Given a graph, its hyperbolicity is a measure of how close its distance distribution is to the
one of a tree. This parameter has gained recent attention in the analysis of some graph …

A graph is called $\alpha_i $-metric ($ i\in {\cal N} $) if it satisfies the following $\alpha_i $-
metric property for every vertices $ u, w, v $ and $ x $: if a shortest path between $ u $ and …

The Gromov hyperbolicity is an important parameter for analyzing complex networks which
expresses how the metric structure of a network looks like a tree. It is for instance used to …

In this paper, we study Gromov hyperbolicity and related parameters, that represent how
close (locally) a metric space is to a tree from a metric point of view. The study of Gromov …

A graph is Helly if every family of pairwise intersecting balls has a nonempty common
intersection. The class of Helly graphs is the discrete analogue of the class of hyperconvex …

Hyperbolicity is a distance-based measure of how close a given graph is to being a tree.
Due to its relevance in modeling real-world networks, hyperbolicity has seen intensive …

Hyperbolicity is a measure of the tree-likeness of a graph from a metric perspective.
Recently, it has been used to classify complex networks depending on their underlying …

The δ-hyperbolicity of a graph is defined by a simple 4-point condition: for any four vertices
u, v, w, and x, the two larger of the distance sums d (u, v)+ d (w, x), d (u, w)+ d (v, x), and d (u …