arXiv subjects

Faisal N. Abu-Khzam

Publications and source records attributed to Faisal N. Abu-Khzam.

At least 19 recordsLinked to original sources

arXiv2026

On the Complexity of Vertex-Splitting Into an Interval Graph

Vertex splitting is a graph modification operation in which a vertex is replaced by multiple vertices such that the union of their neighborhoods equals the neighborhood of the original vertex. We introduce and study vertex splitting as a graph modification operation for transforming graphs into interval graphs. Given a graph $G$ and an integer $k$, we consider the problem of deciding whether $G$ can be transformed into an interval graph using at most $k$ vertex splits. We prove that this problem is NP-hard, even when the input is restricted to subcubic planar bipartite graphs. We further observe that vertex splitting differs fundamentally from vertex and edge deletions as graph modification operations when the objective is to obtain a chordal graph, even for graphs with maximum independent set size at most two. On the positive side, we give a polynomial-time algorithm for transforming, via a minimum number of vertex splits, a given graph into a disjoint union of paths, and that splitting triangle free graphs into unit interval graphs is also solvable in polynomial time.

cs.CC↗

arXiv2025

Bicluster Editing with Overlaps: A Vertex Splitting Approach

The BiCluster Editing problem aims at editing a given bipartite graph into a disjoint union of bicliques via a minimum number of edge deletion or addition operations. As a graph-based model for data clustering, the problem aims at a partition of the input dataset, which cannot always obtain meaningful clusters when some data elements are expected to belong to more than one cluster each. To address this limitation, we introduce the Bicluster Editing with Vertex Splitting problem (BCEVS) which consists of finding a minimum sequence of edge editions and vertex splittings such that the resulting graph is a disjoint union of bicliques. The vertex splitting operation consists of replacing a vertex $v$ with two vertices whose union of neighborhoods is the neighborhood of $v$. We also introduce the problem of Bicluster Editing with One-Sided Vertex Splitting (BCEOVS) where we restrict the splitting operations to the only one set of the two sets forming the bipartition. We prove that the two problems are NP-complete even when restricted to bipartite planar graphs of maximum degree three. Moreover, assuming the {\sc Exponential Time Hypothesis} holds, there is no $2^{o(n)}n^{O(1)}$-time (resp. $2^{o(\sqrt{n})}n^{O(1)}$-time) algorithm for BCEVS and BCEOVS on bipartite (resp. planar) graphs with maximum degree three, where $n$ is the number of vertices of the graph. Furthermore we prove both problems are APX-hard and solvable in polynomial time on trees. On the other hand, we prove that BCEOVS is fixed-parameter tractable with respect to solution size by showing that it admits a polynomial size kernel.

cs.DS↗

arXiv2025

On the Complexity of Claw-Free Vertex Splitting

Vertex splitting consists of taking a vertex $v$ in a graph and replacing it with two non-adjacent vertices whose combined neighborhoods is the neighborhood of $v$. The split is said to be exclusive when these neighborhoods are disjoint. In the Claw-Free (Exclusive) Vertex Splitting problem, we are given a graph $G$ and an integer $k$, and we are asked if we can perform at most $k$ (exclusive) vertex splits to obtain a claw-free graph. We consider the complexity of Claw-Free Exclusive Vertex Splitting and prove it to be NP-complete in general, while admitting a polynomial-time algorithm when the input graph has maximum degree 4. This result settles an open problem posed in [Firbas \& Sorge, ISAAC 2024]. We also show that our results can be generalized to $K_{1,c}$-Free Vertex Splitting for all $c \geq 3$.

cs.CC↗

arXiv2025

A Linear Kernel for Planar Vector Domination

Given a graph $G$, an integer $k\geq 0$, and a non-negative integral function $f:V(G) \rightarrow \mathcal{N}$, the Vector Domination problem asks whether a set $S$ of vertices, of cardinality $k$ or less, exists in $G$ so that every vertex $v \in V(G)\setminus S$ has at least $f(v)$ neighbors in $S$. The problem generalizes several domination problems and it has also been shown to generalize Bounded-Degree Vertex Deletion (BDVD). In this paper, the parameterized version of Vector Domination is studied when the input graph is planar. A linear problem kernel is presented. A direct consequence is a kernel bound for BDVD that is linear in the parameter $k$ only. Previously known bounds are functions of both the target degree and the input parameter.

math.CO↗

arXiv2025

On the Complexity of 2-club Cluster Editing with Vertex Splitting

Editing a graph to obtain a disjoint union of s-clubs is one of the models for correlation clustering, which seeks a partition of the vertex set of a graph so that elements of each resulting set are close enough according to some given criterion. For example, in the case of editing into s-clubs, the criterion is proximity since any pair of vertices (in an s-club) are within a distance of s from each other. In this work we consider the vertex splitting operation, which allows a vertex to belong to more than one cluster. This operation was studied as one of the parameters associated with the Cluster Editing problem. We study the complexity and parameterized complexity of the s-Club Cluster Edge Deletion with Vertex Splitting and s-Club Cluster Vertex Splitting problems. Both problems are shown to be NP-Complete and APX-hard. On the positive side, we show that both problems are Fixed-Parameter Tractable with respect to the number of allowed editing operations and that s-Club Cluster Vertex Splitting is solvable in polynomial-time on the class of forests.

cs.DS↗

arXiv2024

Correlation Clustering with Overlap: a Heuristic Graph Editing Approach

Correlation clustering seeks a partition of the vertex set of a given graph/network into groups of closely related, or just close enough, vertices so that elements of different groups are not close to each other. The problem has been previously modeled and studied as a graph editing problem, namely Cluster Editing, which assumes that closely related data elements must be adjacent. As such, the main objective (of the Cluster Editing problem) is to turn clusters into cliques as a way to identify them. This is to be obtained via two main edge editing operations: additions and deletions. There are two problems with the Cluster Editing model that we seek to address in this paper. First, ``closely'' related does not necessarily mean ``directly'' related. So closeness should be measured by relatively short distance. As such, we seek to turn clusters into (sub)graphs of small diameter. Second, in real applications, a data element can belong, or have roles, in multiple groups. In some cases, without allowing data elements to belong to more than one cluster each, makes it hard to achieve any clustering via classical partition-based methods. We address this latter problem by allowing vertex cloning, also known as vertex splitting. Heuristic methods for the introduced problem are presented along with experimental results showing the effectiveness of the proposed model and algorithmic approach.

cs.SI↗

arXiv2024

Domination in Diameter-Two Graphs and the 2-Club Cluster Vertex Deletion Parameter

The s-club cluster vertex deletion number of a graph, or sccvd, is the minimum number of vertices whose deletion results in a disjoint union of s-clubs, or graphs whose diameter is bounded above by s. We launch a study of several domination problems on diameter-two graphs, or 2-clubs, and study their parameterized complexity with respect to the 2ccvd number as main parameter. We further propose to explore the class of problems that become solvable in sub-exponential time when the running time is independent of some input parameter. Hardness of problems for this class depends on the Exponential-Time Hypothesis. We give examples of problems that are in the proposed class and problems that are hard for it.

cs.CC↗

arXiv2023

Pack and Measure: An Effective Approach for Influence Propagation in Social Networks

The Influence Maximization problem under the Independent Cascade model (IC) is considered. The problem asks for a minimal set of vertices to serve as "seed set" from which a maximum influence propagation is expected. New seed-set selection methods are introduced based on the notions of a $d$-packing and vertex centrality. In particular, we focus on selecting seed-vertices that are far apart and whose influence-values are the highest in their local communities. Our best results are achieved via an initial computation of a $d$-Packing followed by selecting either vertices of high degree or high centrality in their respective closed neighborhoods. This overall "Pack and Measure" approach proves highly effective as a seed selection method.

cs.SI↗

arXiv2023

Concise Fuzzy Planar Embedding of Graphs: a Dimensionality Reduction Approach

The enormous amount of data to be represented using large graphs exceeds in some cases the resources of a conventional computer. Edges in particular can take up a considerable amount of memory as compared to the number of nodes. However, rigorous edge storage might not always be essential to be able to draw the needed conclusions. A similar problem takes records with many variables and attempts to extract the most discernible features. It is said that the ``dimension'' of this data is reduced. Following an approach with the same objective in mind, we can map a graph representation to a $k$-dimensional space and answer queries of neighboring nodes mainly by measuring Euclidean distances. The accuracy of our answers would decrease but would be compensated for by fuzzy logic which gives an idea about the likelihood of error. This method allows for reasonable representation in memory while maintaining a fair amount of useful information, and allows for concise embedding in $k$-dimensional Euclidean space as well as solving some problems without having to decompress the graph. Of particular interest is the case where $k=2$. Promising highly accurate experimental results are obtained and reported.

cs.AI↗

arXiv2023

Cluster Editing with Vertex Splitting

Cluster Editing, also known as Correlation Clustering, is a well-studied graph modification problem. In this problem, one is given a graph and the task is to perform up to $k$ edge additions or deletions to transform it into a cluster graph, i.e., a graph consisting of a disjoint union of cliques. However, in real-world networks, clusters are often overlapping. For example in social networks, a person might belong to several communities - e.g. those corresponding to work, school, or neighborhood. Other strong motivations come from biological network analysis and from language networks. Trying to cluster words with similar usage in the latter can be confounded by homonyms, that is, words with multiple meanings like "bat." In this paper, we introduce a new variant of Cluster Editing whereby a vertex can be split into two or more vertices. First used in the context of graph drawing, this operation allows a vertex $v$ to be replaced by two vertices whose combined neighborhood is the neighborhood of $v$ (and thus $v$ can belong to more than one cluster). We call the new problem Cluster Editing with Vertex Splitting and we initiate the study of it. We show that it is NP-complete and fixed-parameter tractable when parameterized by the total number $k$ of allowed vertex-splitting and edge-editing operations. In particular, we obtain an $O(2^{9k log k} + n + m)$-time algorithm and a $6k$-vertex kernel.

cs.CC↗

arXiv2022

Roman Census: Enumerating and Counting Roman Dominating Functions on Graph Classes

The concept of Roman domination has recently been studied concerning enumerating and counting (WG 2022). It has been shown that minimal Roman dominating functions can be enumerated with polynomial delay, contrasting what is known about minimal dominating sets. The running time of the algorithm could be estimated as $\mathcal{O}(1.9332^n)$ on general graphs of order $n$. In this paper, we focus on special graph classes. More specifically, for chordal graphs, we present an enumeration algorithm running in time $\mathcal{O}(1.8940^n)$. For interval graphs, we can lower this time further to $\mathcal{O}(1.7321^n)$. Interestingly, this also matches (exactly) the known lower bound. We can also provide a matching lower and upper bound for forests, which is (incidentally) the same, namely $\mathcal{O}(\sqrt{3}^n)$. Furthermore, we show an enumeration algorithm running in time $\mathcal{O}(1.4656^n)$ for split graphs and for cobipartite graphs. Our approach also allows to give concrete formulas for counting minimal Roman dominating functions on special graph families like paths.

cs.CC↗

arXiv2022

Minimal Roman Dominating Functions: Extensions and Enumeration

Roman domination is one of the many variants of domination that keeps most of the complexity features of the classical domination problem. We prove that Roman domination behaves differently in two aspects: enumeration and extension. We develop non-trivial enumeration algorithms for minimal Roman domination functions with polynomial delay and polynomial space. Recall that the existence of a similar enumeration result for minimal dominating sets is open for decades. Our result is based on a polynomial-time algorithm for Extension Roman Domination: Given a graph $G = (V,E)$ and a function $f:V\to\{0,1,2\}$, is there a minimal Roman domination function $\Tilde{f}$ with $f\leq \Tilde{f}$? Here, $\leq$ lifts $0< 1< 2$ pointwise; minimality is understood in this order. Our enumeration algorithm is also analyzed from an input-sensitive viewpoint, leading to a run-time estimate of $\Oh(\RomanUpperbound^n)$ for graphs of order n; this is complemented by a lower bound example of $Ω(\RomanLowerbound^n)$.

cs.DS↗

arXiv2021

A Multi-Objective Degree-Based Network Anonymization Approach

Enormous amounts of data collected from social networks or other online platforms are being published for the sake of statistics, marketing, and research, among other objectives. The consequent privacy and data security concerns have motivated the work on degree-based data anonymization. We propose and study a new multi-objective anonymization approach that generalizes the known degree anonymization problem and attempts at improving it as a more realistic model for data security/privacy. Our suggested model guarantees a convenient privacy level based on modifying the degrees in a way that respects some given local restrictions, per node, such that the total modifications at the global level (in the whole graph/network) are bounded by some given value. The corresponding multi-objective graph realization approach is solved using Integer Linear Programming to obtain the best possible solutions. Our experimental studies provide empirical evidence of the effectiveness of the new approach; by specifically showing that the introduced anonymization algorithm has a negligible effect on the way nodes are clustered, thereby preserving valuable network information while significantly improving data privacy.

cs.CR↗

arXiv2021

A Note on the Maximum Number of Minimal Connected Dominating Sets in a Graph

We prove constructively that the maximum possible number of minimal connected dominating sets in a connected undirected graph of order $n$ is in $Ω(1.489^n)$. This improves the previously known lower bound of $Ω(1.4422^n)$ and reduces the gap between lower and upper bounds for input-sensitive enumeration of minimal connected dominating sets in general graphs as well as some special graph classes.

math.CO↗

arXiv2021

An Improved Fixed-Parameter Algorithm for 2-Club Cluster Edge Deletion

A 2-club is a graph of diameter at most two. In the decision version of the parametrized {\sc 2-Club Cluster Edge Deletion} problem, an undirected graph $G$ is given along with an integer $k\geq 0$ as parameter, and the question is whether $G$ can be transformed into a disjoint union of 2-clubs by deleting at most $k$ edges. A simple fixed-parameter algorithm solves the problem in $\mathcal{O}^*(3^k)$, and a decade-old algorithm was claimed to have an improved running time of $\mathcal{O}^*(2.74^k)$ via a sophisticated case analysis. Unfortunately, this latter algorithm suffers from a flawed branching scenario. In this paper, an improved fixed-parameter algorithm is presented with a running time in $\mathcal{O}^*(2.695^k)$.

cs.DS↗

arXiv2020

Graph Minors Meet Machine Learning: the Power of Obstructions

Computational intractability has for decades motivated the development of a plethora of methodologies that mainly aimed at a quality-time trade-off. The use of Machine Learning techniques has finally emerged as one of the possible tools to obtain approximate solutions to ${\cal NP}$-hard combinatorial optimization problems. In a recent article, Dai et al. introduced a method for computing such approximate solutions for instances of the Vertex Cover problem. In this paper we consider the effectiveness of selecting a proper training strategy by considering special problem instances called "obstructions" that we believe carry some intrinsic properties of the problem itself. Capitalizing on the recent work of Dai et al. on the Vertex Cover problem, and using the same case study as well as 19 other problem instances, we show the utility of using obstructions for training neural networks. Experiments show that training with obstructions results in a huge reduction in number of iterations needed for convergence, thus gaining a substantial reduction in the time needed for training the model.

cs.AI↗

arXiv2019

Partitioning a graph into degenerate subgraphs

Let $G = (V, E)$ be a connected graph with maximum degree $k\geq 3$ distinct from $K_{k+1}$. Given integers $s \geq 2$ and $p_1,\ldots,p_s\geq 0$, $G$ is said to be $(p_1, \dots, p_s)$-partitionable if there exists a partition of $V$ into sets~$V_1,\ldots,V_s$ such that $G[V_i]$ is $p_i$-degenerate for $i\in\{1,\ldots,s\}$. In this paper, we prove that we can find a $(p_1, \dots, p_s)$-partition of $G$ in $O(|V| + |E|)$-time whenever $1\geq p_1, \dots, p_s \geq 0$ and $p_1 + \dots + p_s \geq k - s$. This generalizes a result of Bonamy et al. (MFCS, 2017) and can be viewed as an algorithmic extension of Brooks' theorem and several results on vertex arboricity of graphs of bounded maximum degree. We also prove that deciding whether $G$ is $(p, q)$-partitionable is $\mathbb{NP}$-complete for every $k \geq 5$ and pairs of non-negative integers $(p, q)$ such that $(p, q) \not = (1, 1)$ and $p + q = k - 3$. This resolves an open problem of Bonamy et al. (manuscript, 2017). Combined with results of Borodin, Kostochka and Toft (\emph{Discrete Mathematics}, 2000), Yang and Yuan (\emph{Discrete Mathematics}, 2006) and Wu, Yuan and Zhao (\emph{Journal of Mathematical Study}, 1996), it also settles the complexity of deciding whether a graph with bounded maximum degree can be partitioned into two subgraphs of prescribed degeneracy.

cs.DM↗

arXiv2019

A Dynamically Turbo-Charged Greedy Heuristic for Graph Coloring

We introduce a dynamic version of the graph coloring problem and prove its fixed-parameter tractability with respect to the edit-parameter. This is used to present a {\em turbo-charged} heuristic for the problem that works by combining the turbo-charging technique with other standard heuristic tools, including greedy coloring. The recently introduced turbo-charging idea is further enhanced in this paper by introducing a dynamic version of the so called {\em moment of regret} and {\em rollback points}. Experiments comparing our turbo-charging algorithm to other heuristics demonstrate its effectiveness. Our algorithm often produced results that were either exact or better than all the other available heuristics.

cs.DS↗