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Interactions in many real-world phenomena can be explained by a strong hierarchical structure. Typically, this structure or ranking is not known; instead we only have observed outcomes of the interactions, and the goal is to infer the…

Data Structures and Algorithms · Computer Science 2019-04-24 Nikolaj Tatti

Listing k-cliques plays a fundamental role in various data mining tasks, such as community detection and mining of cohesive substructures. Existing algorithms for the k-clique listing problem are built upon a general framework, which finds…

Databases · Computer Science 2025-02-04 Yehyun Nam , Jihoon Jang , Kunsoo Park , Jianye Yang , Cheng Long

Finding a Maximum Clique is a classic property test from graph theory; find any one of the largest complete subgraphs in an Erd\"os-R\'enyi G(N, p) random graph. We use Maximum Clique to explore the structure of the problem as a function of…

Disordered Systems and Neural Networks · Physics 2023-05-26 Raffaele Marino , Scott Kirkpatrick

Counting the frequency of small subgraphs is a fundamental technique in network analysis across various domains, most notably in bioinformatics and social networks. The special case of triangle counting has received much attention. Getting…

Data Structures and Algorithms · Computer Science 2014-11-19 Madhav Jha , C. Seshadhri , Ali Pinar

The maximum clique problem is a well known NP-Hard problem with applications in data mining, network analysis, information retrieval and many other areas related to the World Wide Web. There exist several algorithms for the problem with…

Data Structures and Algorithms · Computer Science 2014-12-01 Bharath Pattabiraman , Md. Mostofa Ali Patwary , Assefaw H. Gebremedhin , Wei-keng Liao , Alok Choudhary

We give new, improved bounds for approximating the sparsest cut value or in other words the conductance $\phi$ of a graph in the CONGEST model. As our main result, we present an algorithm running in $O(\log^2 n/\phi)$ rounds in which every…

Data Structures and Algorithms · Computer Science 2025-08-28 Yannic Maus , Tijn de Vos

We study efficient algorithms for recovering cliques in dense random intersection graphs (RIGs). In this model, $d = n^{\Omega(1)}$ cliques of size approximately $k$ are randomly planted by choosing the vertices to participate in each…

Data Structures and Algorithms · Computer Science 2026-04-13 Andreas Göbel , Janosch Ruff , Leon Schiller

Connected clustering denotes a family of constrained clustering problems in which we are given a distance metric and an undirected connectivity graph $G$ that can be completely unrelated to the metric. The aim is to partition the $n$…

Data Structures and Algorithms · Computer Science 2025-11-25 Jan Eube , Heiko Röglin

The dominating set problem and its generalization, the distance-$r$ dominating set problem, are among the well-studied problems in the sequential settings. In distributed models of computation, unlike for domination, not much is known about…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-10-08 Saeed Akhoondian Amiri , Ben Wiederhake

Graph matching aims to find correspondences between two graphs. This paper integrates several well-known graph matching algorithms into a framework: the constrained gradient method. The primary difference among these algorithms lies in…

Combinatorics · Mathematics 2024-12-11 Binrui Shen , Qiang Niu , Shengxin Zhu

The sparsest cut problem consists of identifying a small set of edges that breaks the graph into balanced sets of vertices. The normalized cut problem balances the total degree, instead of the size, of the resulting sets. Applications of…

Social and Information Networks · Computer Science 2017-02-17 Arlei Silva , Ambuj Singh , Ananthram Swami

We provide CONGEST model algorithms for approximating minimum weighted vertex cover and the maximum weighted matching. For bipartite graphs, we show that a $(1+\varepsilon)$-approximate weighted vertex cover can be computed…

Data Structures and Algorithms · Computer Science 2023-08-09 Salwa Faour , Marc Fuchs , Fabian Kuhn

The mixing time of a graph is an important metric, which is not only useful in analyzing connectivity and expansion properties of the network, but also serves as a key parameter in designing efficient algorithms. We present an efficient…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-10-19 Anisur Rahaman Molla , Gopal Pandurangan

Proximity graph-based methods have emerged as a leading paradigm for approximate nearest neighbor (ANN) search in the system community. This paper presents fresh insights into the theoretical foundation of these methods. We describe an…

Data Structures and Algorithms · Computer Science 2025-09-10 Shangqi Lu , Yufei Tao

We present new distributed algorithms for constructing a Steiner Forest in the CONGEST model. Our deterministic algorithm finds, for any given constant $\epsilon>0$, a $(2+\epsilon)$-approximation in $\tilde{O}(sk+\sqrt{\min(st,n)})$…

Distributed, Parallel, and Cluster Computing · Computer Science 2014-05-09 Christoph Lenzen , Boaz Patt-Shamir

We describe a polynomial-time algorithm which, given a graph $G$ with treewidth $t$, approximates the pathwidth of $G$ to within a ratio of $O(t\sqrt{\log t})$. This is the first algorithm to achieve an $f(t)$-approximation for some…

Data Structures and Algorithms · Computer Science 2023-03-13 Carla Groenland , Gwenaël Joret , Wojciech Nadara , Bartosz Walczak

We study distributed algorithms for some fundamental problems in data summarization. Given a communication graph $G$ of $n$ nodes each of which may hold a value initially, we focus on computing $\sum_{i=1}^N g(f_i)$, where $f_i$ is the…

Data Structures and Algorithms · Computer Science 2019-08-07 Hsin-Hao Su , Hoa T. Vu

This work considers the problem of output-sensitive listing of occurrences of $2k$-cycles for fixed constant $k\geq 2$ in an undirected host graph with $m$ edges and $t$ $2k$-cycles. Recent work of Jin and Xu (and independently Abboud,…

Data Structures and Algorithms · Computer Science 2024-12-16 Virginia Vassilevska Williams , Alek Westover

We propose a fast approximate algorithm for large graph matching. A new projected fixed-point method is defined and a new doubly stochastic projection is adopted to derive the algorithm. Previous graph matching algorithms suffer from high…

Computer Vision and Pattern Recognition · Computer Science 2012-08-13 Yao Lu , Kaizhu Huang , Cheng-Lin Liu

A $t$-ruling set of a graph $G = (V, E)$ is a vertex-subset $S \subseteq V$ that is independent and satisfies the property that every vertex $v \in V$ is at a distance of at most $t$ from some vertex in $S$. A \textit{maximal independent…

Distributed, Parallel, and Cluster Computing · Computer Science 2012-07-16 Kishore Kothapalli , Sriram Pemmaraju
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