Results 41 to 50 of about 24,599 (177)

A Characterization for 2-Self-Centered Graphs

open access: yesDiscussiones Mathematicae Graph Theory, 2018
A graph is called 2-self-centered if its diameter and radius both equal to 2. In this paper, we begin characterizing these graphs by characterizing edge-maximal 2-self-centered graphs via their complements.
Shekarriz Mohammad Hadi   +2 more
doaj   +1 more source

Partitioning the vertex set of a bipartite graph into complete bipartite subgraphs [PDF]

open access: yesDiscrete Mathematics & Theoretical Computer Science, 2014
Graph Theory Given a graph and a positive integer k, the biclique vertex-partition problem asks whether the vertex set of the graph can be partitioned into at most k bicliques (connected complete bipartite subgraphs). It is known that this problem is NP-complete for bipartite graphs.
openaire   +4 more sources

Random algebraic construction of extremal graphs [PDF]

open access: yes, 2015
In this expository paper, we present a motivated construction of large graphs not containing a given complete bipartite subgraph. The key insight is that the algebraic constructions yield very non-smooth probability distributions.Comment: 8 ...
Bukh, Boris
core  

Another Proof of the Generalized Tutte—Berge Formula for f $f$‐Bounded Subgraphs

open access: yesJournal of Graph Theory, EarlyView.
ABSTRACT Given a nonnegative integer weight f ( v ) $f(v)$ for each vertex v $v$ in a multigraph G $G$, an f $f$‐bounded subgraph of G $G$ is a multigraph H $H$ contained in G $G$ such that d H ( v ) ≤ f ( v ) ${d}_{H}(v)\le f(v)$ for all v ∈ V ( G ) $v\in V(G)$.
Zishen Qu, Douglas B. West
wiley   +1 more source

Star-Supermagic Decompositions of the Complete Bipartite Graph Minus a One-Factor

open access: yesInternational Journal of Mathematics and Mathematical Sciences, 2017
Let G be a graph and let H be a subgraph of G. Assume that G has an H-decomposition T={H1,H2,…,Ht} such that Hi≅H for all 1≤i≤t. An H-supermagic decomposition of G is a bijection f:V(G)∪E(G)→1,2,…,VG+EG such that ∑v∈V(Hi)f(v)+∑e∈E(Hi)f(e) is a constant k
Tanawat Wichianpaisarn, Uthoomporn Mato
doaj   +1 more source

Robustness Assessment of Public Transport Networks in Various Graph Representations: Systematic Review, Decision Support, and Case Study

open access: yesNetworks, EarlyView.
ABSTRACT The analysis of certain properties of the underlying graph of a public transport network generates insights about the network's structure. Hereby, the choice of the graph representation depends on a trade‐off between complexity reduction and information preservation to adequately model a public transport network.
Michael Palk   +2 more
wiley   +1 more source

Generation of Gray Codes Through the Rough Identity–Summand Graph of Filters of A Rough bi–Heyting Algebra

open access: yesInternational Journal of Applied Mathematics and Computer Science
This paper introduces the concept of filters in a rough bi-Heyting algebra. The rough bi-Heyting algebra defined through the rough semiring offers interesting properties.
Praba Bashyam   +1 more
doaj   +1 more source

Total $k$-rainbow domination subdivision number in graphs [PDF]

open access: yesComputer Science Journal of Moldova, 2020
A total $k$-rainbow dominating function (T$k$RDF) of $G$ is a function $f$ from the vertex set $V(G)$ to the set of all subsets of the set $\{1,\ldots,k\}$ such that (i) for any vertex $v\in V(G)$ with $f(v)=\emptyset$ the condition $\bigcup_{u \in N(v ...
Rana Khoeilar   +3 more
doaj  

On vertex stability with regard to complete bipartite subgraphs

open access: yesDiscussiones Mathematicae Graph Theory, 2010
A graph G is called (H; k)-vertex stable if G contains a subgraph isomorphic to H ever after removing any of its k vertices. Q(H; k) denotes the minimum size among the sizes of all (H; k)-vertex stable graphs. In this paper we complete the characterization of (Km;n; 1)vertex stable graphs with minimum size.
Aneta Dudek, Andrzej Żak
openaire   +1 more source

Generating Compressed Counterfactual Hard Negative Samples for Graph Contrastive Learning

open access: yesCAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Graph contrastive learning (GCL) relies on acquiring high‐quality positive and negative samples to learn the structural semantics of the input graph. Previous approaches typically sampled negative samples from the same training batch or an irrelevant external graph.
Haoran Yang   +7 more
wiley   +1 more source

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