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The distinguishing index of a simple graph $G$, denoted by $D'(G)$, is the least number of labels in an edge labeling of $G$ not preserved by any non-trivial automorphism. It was conjectured by Pil\'sniak (2015) that for any 2-connected…

Combinatorics · Mathematics 2017-02-14 Saeid Alikhani , Samaneh Soltani

The unit interval vertex deletion problem asks for a set of at most $k$ vertices whose deletion from an $n$-vertex graph makes it a unit interval graph. We develop an $O(k^4)$-vertex kernel for the problem, significantly improving the…

Data Structures and Algorithms · Computer Science 2016-07-06 Yuping Ke , Yixin Cao , Xiating Ouyang , Jianxin Wang

In this paper, we present two main results. First, by only one conjecture (Conjecture 2.9) for recognizing a vertex symmetric graph, which is the hardest task for our problem, we construct an algorithm for finding an isomorphism between two…

Data Structures and Algorithms · Computer Science 2017-06-29 Caishi Fang

How efficiently can we find an unknown graph using distance queries between its vertices? We assume that the unknown graph is connected, unweighted, and has bounded degree. The goal is to find every edge in the graph. This problem admits a…

Data Structures and Algorithms · Computer Science 2021-12-14 Claire Mathieu , Hang Zhou

We introduce the class of interval $H$-graphs, which is the generalization of interval graphs, particularly interval bigraphs. For a fixed graph $H$ with vertices $a_1,a_2,\dots,a_k$, we say that an input graph $G$ with given partition…

Discrete Mathematics · Computer Science 2025-03-04 Haiko Müller , Arash Rafiey

In this paper we extend the work of Rautenbach and Szwarcfiter by giving a structural characterization of graphs that can be represented by the intersection of unit intervals that may or may not contain their endpoints. A characterization…

Combinatorics · Mathematics 2014-05-19 Alan Shuchat , Randy Shull , Ann N. Trenk , Lee C. West

We present new quantum algorithms for Triangle Finding improving its best previously known quantum query complexities for both dense and spare instances.For dense graphs on $n$ vertices, we get a query complexity of $O(n^{5/4})$ without any…

Quantum Physics · Physics 2016-10-13 Titouan Carette , Mathieu Laurière , Frédéric Magniez

The graph isomorphism problem is a main problem which has numerous applications in different fields. Thus, finding an efficient and easy to implement method to discriminate non-isomorphic graphs is valuable. In this paper, a new method is…

Combinatorics · Mathematics 2016-11-08 Ameneh Farhadian

The class of 2-interval graphs has been introduced for modelling scheduling and allocation problems, and more recently for specific bioinformatic problems. Some of those applications imply restrictions on the 2-interval graphs, and justify…

Discrete Mathematics · Computer Science 2008-02-04 Philippe Gambette , Stéphane Vialette

In this short survey article, we present an elementary, yet quite powerful, method of enumerating independent sets in graphs. This method was first employed more than three decades ago by Kleitman and Winston and has subsequently been used…

Combinatorics · Mathematics 2014-12-03 Wojciech Samotij

We explore what could make recognition of particular intersection-defined classes hard. We focus mainly on unit grid intersection graphs (UGIGs), i.e., intersection graphs of unit-length axis-aligned segments and grid intersection graphs…

Computational Geometry · Computer Science 2022-01-24 Irina Mustata , Martin Pergel

Large graphs are difficult to represent, visualize, and understand. In this paper, we introduce "gate graph" - a new approach to perform graph simplification. A gate graph provides a simplified topological view of the original graph.…

Social and Information Networks · Computer Science 2016-11-18 Ning Ruan , Ruoming Jin , Yan Huang

A popular way to define or characterize graph classes is via forbidden subgraphs or forbidden minors. These characterizations play a key role in graph theory, but they rarely lead to efficient algorithms to recognize these classes. In…

Data Structures and Algorithms · Computer Science 2023-02-24 Guillaume Ducoffe , Laurent Feuilloley , Michel Habib , François Pitois

We present a sound and complete algorithm for recovering causal graphs from observed, non-interventional data, in the possible presence of latent confounders and selection bias. We rely on the causal Markov and faithfulness assumptions and…

Artificial Intelligence · Computer Science 2020-12-25 Raanan Y. Rohekar , Yaniv Gurwicz , Shami Nisimov , Gal Novik

We obtain new lower bounds for the independence number of $K_r$-free graphs and linear $k$-uniform hypergraphs in terms of the degree sequence. This answers some old questions raised by Caro and Tuza \cite{CT91}. Our proof technique is an…

Combinatorics · Mathematics 2011-02-25 Kunal Dutta , Dhruv Mubayi , C. R. Subramanian

The distance ideals of graphs are algebraic invariants that generalize the Smith normal form (SNF) and the spectrum of several distance matrices associated with a graph. In general, distance ideals are not monotone under taking induced…

We revisit the algorithmic problem of finding a triangle in a graph (\textsc{Triangle Detection}), and examine its relation to other problems such as \textsc{3Sum}, \textsc{Independent Set}, and \textsc{Graph Coloring}. We obtain several…

Data Structures and Algorithms · Computer Science 2024-02-13 Adrian Dumitrescu

A cocomparability graph is a graph whose complement admits a transitive orientation. An interval graph is the intersection graph of a family of intervals on the real line. In this paper we investigate the relationships between interval and…

Discrete Mathematics · Computer Science 2016-11-08 Jérémie Dusart , Michel Habib , Derek G. Corneil

Graphs are versatile tools for representing structured data. As a result, a variety of machine learning methods have been studied for graph data analysis. Although many such learning methods depend on the measurement of differences between…

Machine Learning · Statistics 2021-06-18 Tomoki Yoshida , Ichiro Takeuchi , Masayuki Karasuyama

Evaluating graphs learned by causal discovery algorithms is difficult: The number of edges that differ between two graphs does not reflect how the graphs differ with respect to the identifying formulas they suggest for causal effects. We…

Machine Learning · Statistics 2024-07-12 Leonard Henckel , Theo Würtzen , Sebastian Weichwald