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Testing a graph on 2-vertex- and 2-edge-connectivity are two fundamental algorithmic graph problems. For both problems, different linear-time algorithms with simple implementations are known. Here, an even simpler linear-time algorithm is…

Data Structures and Algorithms · Computer Science 2012-09-05 Jens M. Schmidt

The min-rank of a digraph was shown by Bar-Yossef et al. (2006) to represent the length of an optimal scalar linear solution of the corresponding instance of the Index Coding with Side Information (ICSI) problem. In this work, the graphs…

Information Theory · Computer Science 2013-03-19 Son Hoang Dau , Vitaly Skachek , Yeow Meng Chee

The graph packing problem is a well-known area in graph theory. We consider a bipartite version and give almost tight conditions on the packability of two bipartite sequences.

Combinatorics · Mathematics 2017-05-03 Bálint Vásárhelyi

The bipartition polynomial of a graph is a generalization of many other graph polynomials, including the domination, Ising, matching, independence, cut, and Euler polynomial. We show in this paper that it is also a powerful tool for proving…

Combinatorics · Mathematics 2017-02-14 Seongmin Ok , Peter Tittmann

The second largest eigenvalue of a graph is an important algebraic parameter which is related with the expansion, connectivity and randomness properties of a graph. Expanders are highly connected sparse graphs. In coding theory, Expander…

Combinatorics · Mathematics 2023-08-23 Machasri Manickam , Kalyani Desikan

For a given $2$-partition $(V_1,V_2)$ of the vertices of a (di)graph $G$, we study properties of the spanning bipartite subdigraph $B_G(V_1,V_2)$ of $G$ induced by those arcs/edges that have one end in each $V_i$. We determine, for all…

Discrete Mathematics · Computer Science 2017-08-01 Jørgen Bang-Jensen , Stéphane Bessy , Frédéric Havet , Anders Yeo

Induced bipartite subgraphs of maximal vertex cardinality are an essential concept for the analysis of graphs. Yet, discovering them in large graphs is known to be computationally hard. Therefore, we consider in this work a weaker notion of…

Artificial Intelligence · Computer Science 2022-11-22 Dominik Dürrschnabel , Tom Hanika , Gerd Stumme

Motivated by problems modeling the spread of infections in networks, in this paper we explore which bipartite graphs are most resilient to widespread infections under various parameter settings. Namely, we study bipartite networks with a…

Data Structures and Algorithms · Computer Science 2018-01-10 Shelby Heinecke , Will Perkins , Lev Reyzin

(Hyper)Graph decomposition is a family of problems that aim to break down large (hyper)graphs into smaller sub(hyper)graphs for easier analysis. The importance of this lies in its ability to enable efficient computation on large and complex…

Data Structures and Algorithms · Computer Science 2023-08-31 Marcelo Fonseca Faraj

Topological drawings are natural representations of graphs in the plane, where vertices are represented by points, and edges by curves connecting the points. Topological drawings of complete graphs and of complete bipartite graphs have been…

Computational Geometry · Computer Science 2017-02-10 Jean Cardinal , Stefan Felsner

Let $G$ be a simple graph with order $n$ and adjacency matrix $\mathbf{A}(G)$. Let $\phi(G; \lambda)=\det(\lambda I-\mathbf{A}(G))=\sum_{i=0}^n\mathbf{a}_i(G)\lambda^{n-i}$ be the characteristic polynomial of $G$, where $\mathbf{a}_i(G)$ is…

Combinatorics · Mathematics 2020-02-11 Shi Cai Gong , Shao Wei Sun

A transitive graph is 2-dimensional if it can be represented as the intersection of two linear orders. Such representations make answering of reachability queries trivial, and allow many problems that are NP-hard on arbitrary graphs to be…

Discrete Mathematics · Computer Science 2019-04-09 Henning Koehler

A graph $G$ is said to be a `set graph' if it admits an acyclic orientation that is also `extensional', in the sense that the out-neighborhoods of its vertices are pairwise distinct. Equivalently, a set graph is the underlying graph of the…

Discrete Mathematics · Computer Science 2015-03-20 Martin Milanič , Romeo Rizzi , Alexandru I. Tomescu

Graph neural networks can be effectively applied to find solutions for many real-world problems across widely diverse fields. The success of graph neural networks is linked to the message-passing mechanism on the graph, however, the…

Machine Learning · Computer Science 2022-01-06 Yan Pang , Chao Liu

We consider the algorithmic problem of finding large \textit{balanced} independent sets in sparse random bipartite graphs, and more generally the problem of finding independent sets with specified proportions of vertices on each side of the…

Data Structures and Algorithms · Computer Science 2023-07-27 Will Perkins , Yuzhou Wang

We investigate topological, combinatorial, statistical, and enumeration properties of finite graphs with high Kolmogorov complexity (almost all graphs) using the novel incompressibility method. Example results are: (i) the mean and variance…

Combinatorics · Mathematics 2007-05-23 Harry Buhrman , Ming Li , John Tromp , Paul Vitanyi

We study the classical problem of computing geometric thickness, i.e., finding a straight-line drawing of an input graph and a partition of its edges into as few parts as possible so that each part is crossing-free. Since the problem is…

Computational Complexity · Computer Science 2024-11-26 Thomas Depian , Simon Dominik Fink , Alexander Firbas , Robert Ganian , Martin Nöllenburg

Generalizing well-known results of Erd\H{o}s and Lov\'asz, we show that every graph $G$ contains a spanning $k$-partite subgraph $H$ with $\lambda{}(H)\geq \lceil{}\frac{k-1}{k}\lambda{}(G)\rceil$, where $\lambda{}(G)$ is the…

Combinatorics · Mathematics 2020-08-13 J. Bang-Jensen , F. Havet , M. Kriesell , A. Yeo

Computer or communication networks are so designed that they do not easily get disrupted under external attack and, moreover, these are easily reconstructible if they do get disrupted. These desirable properties of networks can be measured…

Combinatorics · Mathematics 2011-09-23 T. C. E. Cheng , Yinkui Li , Chuandong Xu , Shenggui Zhang

Supervised learning on graphs is a challenging task due to the high dimensionality and inherent structural dependencies in the data, where each edge depends on a pair of vertices. Existing conventional methods are designed for standard…

Methodology · Statistics 2024-06-27 Cencheng Shen , Shangsi Wang , Alexandra Badea , Carey E. Priebe , Joshua T. Vogelstein