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In this paper we focus on the problem of finding (small) subhypergraphs in a (large) hypergraph. We use this problem to illustrate that reducing hypergraph problems to graph problems by working with the 2-section is not always a reasonable…

TopoDetect is a Python package that allows the user to investigate if important topological features, such as the Degree of the nodes, their Triangle Count, or their Local Clustering Score, are preserved in the embeddings of graph…

Machine Learning · Computer Science 2021-10-11 Maroun Haddad , Mohamed Bouguessa

We present a novel distributed algorithm for counting all four-node induced subgraphs in a big graph. These counts, called the $4$-profile, describe a graph's connectivity properties and have found several uses ranging from bioinformatics…

Social and Information Networks · Computer Science 2016-04-05 Ethan R. Elenberg , Karthikeyan Shanmugam , Michael Borokhovich , Alexandros G. Dimakis

We present proof labeling schemes for graphs with bounded pathwidth that can decide any graph property expressible in monadic second-order (MSO) logic using $O(\log n)$-bit vertex labels. Examples of such properties include planarity,…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-02-04 Dan Alden Baterisna , Yi-Jun Chang

One of the fundamental task in graph data mining is to find a planted community(dense subgraph), which has wide application in biology, finance, spam detection and so on. For a real network data, the existence of a dense subgraph is…

Methodology · Statistics 2021-01-18 Mingao Yuan , Qian Wen

The problem of finding locally dense components of a graph is an important primitive in data analysis, with wide-ranging applications from community mining to spam detection and the discovery of biological network modules. In this paper we…

Databases · Computer Science 2012-02-01 Bahman Bahmani , Ravi Kumar , Sergei Vassilvitskii

Consider the following "local" cut-detection problem in a directed graph: We are given a starting vertex $s$ and need to detect whether there is a cut with at most $k$ edges crossing the cut such that the side of the cut containing $s$ has…

Data Structures and Algorithms · Computer Science 2019-04-23 Sebastian Forster , Liu Yang

One of the major results of [N. Robertson and P. D. Seymour. Graph minors. XIII. The disjoint paths problem. J. Combin. Theory Ser. B, 63(1):65--110, 1995], also known as the weak structure theorem, revealed the local structure of graphs…

Combinatorics · Mathematics 2011-03-01 Archontia C. Giannopoulou , Dimitrios M. Thilikos

We study the problem of testing for community structure in networks using relations between the observed frequencies of small subgraphs. We propose a simple test for the existence of communities based only on the frequencies of three-node…

Methodology · Statistics 2017-10-17 Chao Gao , John Lafferty

Inhomogeneous random graphs are fundamental models for real-world networks, where prescribed degrees are imposed as soft constraints. A common assumption in such models is that the degree distribution follows a power-law, capturing the…

Probability · Mathematics 2026-03-09 Riccardo Michielan , Clara Stegehuis , Bert Zwart

A minimal separating set in a connected topological space $X$ is a subset $L \subset X$ with the property that $X \setminus L$ is disconnected, but if $L^{\prime}$ is a proper subset of $L$, then $X \setminus L^{\prime}$ is connected. Such…

Combinatorics · Mathematics 2025-07-17 Christopher N. Aagaard , J. J. P. Veerman

Contrary to the sequential world, the processes involved in a distributed system do not necessarily know when a computation is globally finished. This paper investigates the problem of the detection of the termination of local computations.…

Distributed, Parallel, and Cluster Computing · Computer Science 2010-01-20 Emmanuel Godard , Yves Métivier , Gerard Tel

Community structure is a commonly observed feature of real networks. The term refers to the presence in a network of groups of nodes (communities) that feature high internal connectivity, but are poorly connected between each other. Whereas…

Applications · Statistics 2021-10-07 Mirko Signorelli , Luisa Cutillo

We study the problem of detecting local geometry in random graphs. We introduce a model $\mathcal{G}(n, p, d, k)$, where a hidden community of average size $k$ has edges drawn as a random geometric graph on $\mathbb{S}^{d-1}$, while all…

Statistics Theory · Mathematics 2026-03-26 Jinho Bok , Shuangping Li , Sophie H. Yu

Local Irregularity Conjecture states that every simple connected graph, except special cacti, can be decomposed into at most three locally irregular graphs, i.e., graphs in which adjacent vertices have different degrees. The connected…

Combinatorics · Mathematics 2025-02-13 Igor Grzelec , Alfréd Onderko , Mariusz Woźniak

The locality of a graph problem is the smallest distance $T$ such that each node can choose its own part of the solution based on its radius-$T$ neighborhood. In many settings, a graph problem can be solved efficiently with a distributed or…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-12-14 Yi-Jun Chang , Jan Studený , Jukka Suomela

We consider the algorithmic decision problem that takes as input an $n$-vertex $k$-uniform hypergraph $H$ with minimum codegree at least $m-c$ and decides whether it has a matching of size $m$. We show that this decision problem is fixed…

Combinatorics · Mathematics 2022-10-25 Jie Han , Peter Keevash

Proof-labeling schemes are known mechanisms providing nodes of networks with certificates that can be verified locally by distributed algorithms. Given a boolean predicate on network states, such schemes enable to check whether the…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-04-26 Laurent Feuilloley , Pierre Fraigniaud

Community detection in graphs has many important and fundamental applications including in distributed systems, compression, image segmentation, divide-and-conquer graph algorithms such as nested dissection, document and word clustering,…

Social and Information Networks · Computer Science 2019-06-18 Ryan A. Rossi , Nesreen K. Ahmed , Eunyee Koh , Sungchul Kim

Graph embedding methods are becoming increasingly popular in the machine learning community, where they are widely used for tasks such as node classification and link prediction. Embedding graphs in geometric spaces should aid the…