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Given a graph $G=(V, E)$ and and a proper labeling $f$ from $V$ to $\{1, ..., n\}$, we define $B(f)$ as the maximum absolute difference between $f(u)$ and $f(v)$ where $(u,v)\in E$. The bandwidth of $G$ is the minimum $B(f)$ for all $f$.…

Data Structures and Algorithms · Computer Science 2012-11-02 Hao-Hsiang Hung

Decomposing a graph into a hierarchical structure via $k$-core analysis is a standard operation in any modern graph-mining toolkit. $k$-core decomposition is a simple and efficient method that allows to analyze a graph beyond its mere…

Data Structures and Algorithms · Computer Science 2020-01-16 Nikolaj Tatti

The Cluster Deletion problem takes a graph $G$ as input and asks for a minimum size set of edges $X$ such that $G-X$ is the disjoint union of complete graphs. An equivalent formulation is the Clique Partition problem, which asks to find a…

Data Structures and Algorithms · Computer Science 2025-09-26 Nicola Galesi , Tony Huynh , Fariba Ranjbar

Cyclic coordinate descent is a classic optimization method that has witnessed a resurgence of interest in machine learning. Reasons for this include its simplicity, speed and stability, as well as its competitive performance on $\ell_1$…

Machine Learning · Computer Science 2015-03-17 Ankan Saha , Ambuj Tewari

Many common graph data mining tasks take the form of identifying dense subgraphs (e.g. clustering, clique-finding, etc). In biological applications, the natural model for these dense substructures is often a complete bipartite graph…

Data Structures and Algorithms · Computer Science 2019-01-28 Kyle Kloster , Blair D. Sullivan , Andrew van der Poel

The family of $(k, \ell)$-sparse graphs, introduced by Lorea, plays a central role in combinatorial optimization and has a wide range of applications, particularly in rigidity theory. A key algorithmic challenge is to compute a…

Data Structures and Algorithms · Computer Science 2025-11-27 Bence Deák , Péter Madarasi

The family of $(k,\ell)$-sparse graphs, introduced by Lorea, plays a central role in combinatorial optimization and has a wide range of applications, particularly in rigidity theory. A key algorithmic problem is to decide whether a given…

Data Structures and Algorithms · Computer Science 2026-04-15 Bence Deák , Péter Madarasi

For the constrained 2-means problem, we present a $O\left(dn+d({1\over\epsilon})^{O({1\over \epsilon})}\log n\right)$ time algorithm. It generates a collection $U$ of approximate center pairs $(c_1, c_2)$ such that one of pairs in $U$ can…

Computational Geometry · Computer Science 2018-08-14 Qilong Feng , Bin Fu

A minimum chain cover (MCC) of a $k$-width directed acyclic graph (DAG) $G = (V, E)$ is a set of $k$ chains (paths in the transitive closure) of $G$ such that every vertex appears in at least one chain in the cover. The state-of-the-art…

Data Structures and Algorithms · Computer Science 2023-05-04 Manuel Caceres

Link streams offer a good model for representing interactions over time. They consist of links $(b,e,u,v)$, where $u$ and $v$ are vertices interacting during the whole time interval $[b,e]$. In this paper, we deal with the problem of…

Data Structures and Algorithms · Computer Science 2024-05-27 Alexis Baudin , Clémence Magnien , Lionel Tabourier

We propose improved exact and heuristic algorithms for solving the maximum weight clique problem, a well-known problem in graph theory with many applications. Our algorithms interleave successful techniques from related work with novel data…

Data Structures and Algorithms · Computer Science 2023-02-02 Roman Erhardt , Kathrin Hanauer , Nils Kriege , Christian Schulz , Darren Strash

Let $G=(V, E)$ be an undirected $n$-vertices $m$-edges graph with non-negative edge weights. In this paper, we present three new algorithms for constructing a $(2k-1)$-stretch distance oracle with $O(n^{1+\frac{1}{k}})$ space. The first…

Data Structures and Algorithms · Computer Science 2026-04-24 Avi Kadria , Liam Roditty

We consider the minimal k-grouping problem: given a graph G=(V,E) and a constant k, partition G into subgraphs of diameter no greater than k, such that the union of any two subgraphs has diameter greater than k. We give a silent…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-07-26 Ajoy K. Datta , Lawrence L. Larmore , Toshimitsu Masuzawa , Yuichi Sudo

In this paper, we consider the problem of finding a cycle of length $2k$ (a $C_{2k}$) in an undirected graph $G$ with $n$ nodes and $m$ edges for constant $k\ge2$. A classic result by Bondy and Simonovits [J.Comb.Th.'74] implies that if $m…

Data Structures and Algorithms · Computer Science 2017-03-31 Søren Dahlgaard , Mathias Bæk Tejs Knudsen , Morten Stöckel

As a fundamental task in graph data management, maximal clique enumeration (MCE) has attracted extensive attention from both academic and industrial communities due to its wide range of applications. However, MCE is very challenging as the…

Databases · Computer Science 2023-11-03 Wen Deng , Weiguo Zheng , Hong Cheng

The minimum degree algorithm is one of the most widely-used heuristics for reducing the cost of solving large sparse systems of linear equations. It has been studied for nearly half a century and has a rich history of bridging techniques…

Data Structures and Algorithms · Computer Science 2023-04-11 Robert Cummings , Matthew Fahrbach , Animesh Fatehpuria

The $k$-Maximum Dispersion Problem with Cardinality Constraints ($k$-MDCC) asks for a partition of a given item set with pairwise dissimilarities into $k$ cardinality-constrained groups such that the minimum pairwise intra-group…

Data Structures and Algorithms · Computer Science 2026-04-28 Nguyen Khoa Tran , Lin Mu , Martin Papenberg , Gunnar W. Klau

In an undirected graph, a $k$-cut is a set of edges whose removal breaks the graph into at least $k$ connected components. The minimum weight $k$-cut can be computed in $O(n^{O(k)})$ time, but when $k$ is treated as part of the input,…

Data Structures and Algorithms · Computer Science 2018-11-20 Kent Quanrud

In the $k$-edge-connected spanning subgraph ($k$ECSS) problem, our goal is to compute a minimum-cost sub-network that is resilient against up to $k$ link failures: Given an $n$-node $m$-edge graph with a cost function on the edges, our goal…

We consider Bernoulli nonadaptive group testing with $k = \Theta(n^\theta)$ defectives, for $\theta \in (0,1)$. The practical definite defectives (DD) detection algorithm is known to be optimal for $\theta \geq 1/2$. We give a new upper…

Information Theory · Computer Science 2017-11-27 Matthew Aldridge