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Hub labeling schemes are popular methods for computing distances on road networks and other large complex networks, often answering to a query within a few microseconds for graphs with millions of edges. In this work, we study their…

Data Structures and Algorithms · Computer Science 2020-10-30 Guillaume Ducoffe

A dynamic graph algorithm is a data structure that answers queries about a property of the current graph while supporting graph modifications such as edge insertions and deletions. Prior work has shown strong conditional lower bounds for…

Data Structures and Algorithms · Computer Science 2023-01-30 Monika Henzinger , Ami Paz , A. R. Sricharan

Planar graphs are known to allow subexponential algorithms running in time $2^{O(\sqrt n)}$ or $2^{O(\sqrt n \log n)}$ for most of the paradigmatic problems, while the brute-force time $2^{\Theta(n)}$ is very likely to be asymptotically…

Computational Geometry · Computer Science 2018-10-12 Édouard Bonnet , Paweł Rzążewski

Many hard graph problems, such as Hamiltonian Cycle, become FPT when parameterized by treewidth, a parameter that is bounded only on sparse graphs. When parameterized by the more general parameter clique-width, Hamiltonian Cycle becomes…

Data Structures and Algorithms · Computer Science 2014-11-24 Sigve Hortemo Sæther

The Path Contraction and Cycle Contraction problems take as input an undirected graph $G$ with $n$ vertices, $m$ edges and an integer $k$ and determine whether one can obtain a path or a cycle, respectively, by performing at most $k$ edge…

Data Structures and Algorithms · Computer Science 2024-03-12 R. Krithika , V. K. Kutty Malu , Prafullkumar Tale

Sublinear time algorithms for approximating maximum matching size have long been studied. Much of the progress over the last two decades on this problem has been on the algorithmic side. For instance, an algorithm of Behnezhad [FOCS'21]…

Data Structures and Algorithms · Computer Science 2022-11-30 Soheil Behnezhad , Mohammad Roghani , Aviad Rubinstein

We develop a novel parallel decomposition strategy for unweighted, undirected graphs, based on growing disjoint connected clusters from batches of centers progressively selected from yet uncovered nodes. With respect to similar previous…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-02-09 Matteo Ceccarello , Andrea Pietracaprina , Geppino Pucci , Eli Upfal

For a finite set $\mathcal{F}$ of graphs, the $\mathcal{F}$-Hitting problem aims to compute, for a given graph $G$ (taken from some graph class $\mathcal{G}$) of $n$ vertices (and $m$ edges) and a parameter $k\in\mathbb{N}$, a set $S$ of…

Data Structures and Algorithms · Computer Science 2025-02-19 Daniel Lokshtanov , Fahad Panolan , Saket Saurabh , Jie Xue , Meirav Zehavi

We present the first truly subcubic, combinatorial algorithm for detecting an induced $4$-cycle in a graph. The running time is $O(n^{2.84})$ on $n$-node graphs, thus separating the task of detecting induced $4$-cycles from detecting…

Data Structures and Algorithms · Computer Science 2026-01-12 Amir Abboud , Shyan Akmal , Nick Fischer

We present improved algorithms for short cycle decomposition of a graph. Short cycle decompositions were introduced in the recent work of Chu et al, and were used to make progress on several questions in graph sparsification. For all…

Data Structures and Algorithms · Computer Science 2019-01-15 Yang P. Liu , Sushant Sachdeva , Zejun Yu

In this paper, we give new, tight subexponential lower bounds for a number of graph embedding problems. We introduce two related combinatorial problems, which we call String Crafting and Orthogonal Vector crafting, and show that these…

Computational Complexity · Computer Science 2016-10-31 Hans L. Bodlaender , Tom C. van der Zanden

Consider a directed or an undirected graph with integral edge weights from the set [-W, W], that does not contain negative weight cycles. In this paper, we introduce a general framework for solving problems on such graphs using matrix…

Data Structures and Algorithms · Computer Science 2012-08-20 Marek Cygan , Harold N. Gabow , Piotr Sankowski

In a seminal paper on finding large matchings in sparse random graphs, Karp and Sipser proposed two algorithms for this task. The second algorithm has been intensely studied, but due to technical difficulties, the first algorithm has…

Combinatorics · Mathematics 2018-11-14 Michael Anastos , Alan Frieze

Betweenness centrality measure assesses the importance of nodes in a graph and has been used in a variety of contexts. Betweenness centrality has also been extended to temporal graphs. Temporal graphs have edges that bear labels according…

Data Structures and Algorithms · Computer Science 2023-06-07 Mehdi Naima , Matthieu Latapy , Clémence Magnien

Finding dense subgraphs is a core problem in graph mining with many applications in diverse domains. At the same time many real-world networks vary over time, that is, the dataset can be represented as a sequence of graph snapshots. Hence,…

Data Structures and Algorithms · Computer Science 2023-08-31 Chamalee Wickrama Arachchi , Nikolaj Tatti

We consider the problem of finding all allowed edges in a bipartite graph $G=(V,E)$, i.e., all edges that are included in some maximum matching. We show that given any maximum matching in the graph, it is possible to perform this…

Discrete Mathematics · Computer Science 2011-07-26 Tamir Tassa

Computing the Euler genus of a graph is a fundamental problem in graph theory and topology. It has been shown to be NP-hard by [Thomassen '89] and a linear-time fixed-parameter algorithm has been obtained by [Mohar '99]. Despite extensive…

Data Structures and Algorithms · Computer Science 2014-12-05 Ken-ichi Kawarabayashi , Anastasios Sidiropoulos

The {\em maximum cardinality} and {\em maximum weight matching} problems can be solved in time $\tilde{O}(m\sqrt{n})$, a bound that has resisted improvement despite decades of research. (Here $m$ and $n$ are the number of edges and…

Data Structures and Algorithms · Computer Science 2011-12-06 Ran Duan , Seth Pettie , Hsin-Hao Su

The fundamental sparsest cut problem takes as input a graph $G$ together with the edge costs and demands, and seeks a cut that minimizes the ratio between the costs and demands across the cuts. For $n$-node graphs~$G$ of treewidth~$k$,…

Data Structures and Algorithms · Computer Science 2024-04-23 Parinya Chalermsook , Matthias Kaul , Matthias Mnich , Joachim Spoerhase , Sumedha Uniyal , Daniel Vaz

We give the first almost-linear time algorithm for computing the \emph{maximal $k$-edge-connected subgraphs} of an undirected unweighted graph for any constant $k$. More specifically, given an $n$-vertex $m$-edge graph $G=(V,E)$ and a…

Data Structures and Algorithms · Computer Science 2023-07-04 Thatchaphol Saranurak , Wuwei Yuan
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