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Given a graph $G = (V, E)$ with $n$ vertices and $m$ edges, the DominatingSet problem asks for a set $D \subseteq V$ of minimal cardinality such that every vertex either is in $D$ or adjacent to a member of $D$. Although there is little…

Data Structures and Algorithms · Computer Science 2025-12-03 Lukas Geis , Alexander Leonhardt , Johannes Meintrup , Ulrich Meyer , Manuel Penschuck , Lukas Retschmeier

In this paper, we relate the problem of finding a maximum clique to the intersection number of the input graph (i.e. the minimum number of cliques needed to edge cover the graph). In particular, we consider the maximum clique problem for…

Discrete Mathematics · Computer Science 2012-04-19 S. Nikoletseas , C. Raptopoulos , P. G. Spirakis

We give fast, simple, and implementable catalytic logspace algorithms for two fundamental graph problems. First, a randomized catalytic algorithm for $s\to t$ connectivity running in $\widetilde{O}(nm)$ time, and a deterministic catalytic…

Data Structures and Algorithms · Computer Science 2025-09-09 James Cook , Edward Pyne

Let $F$ be a set of $n$ objects in the plane and let $G(F)$ be its intersection graph. A balanced clique-based separator of $G(F)$ is a set $S$ consisting of cliques whose removal partitions $G(F)$ into components of size at most $\delta…

Computational Geometry · Computer Science 2021-09-22 Mark de Berg , Sándor Kisfaludi-Bak , Morteza Monemizadeh , Leonidas Theocharous

Many load balancing problems that arise in scientific computing applications ask to partition a graph with weights on the vertices and costs on the edges into a given number of almost equally-weighted parts such that the maximum boundary…

Data Structures and Algorithms · Computer Science 2007-05-23 David Steurer

We present a deterministic (global) mincut algorithm for weighted, undirected graphs that runs in $m^{1+o(1)}$ time, answering an open question of Karger from the 1990s. To obtain our result, we de-randomize the construction of the…

Data Structures and Algorithms · Computer Science 2026-05-07 Jason Li

We give a deterministic algorithm for finding the minimum (weight) cut of an undirected graph on $n$ vertices and $m$ edges using $\text{polylog}(n)$ calls to any maximum flow subroutine. Using the current best deterministic maximum flow…

Data Structures and Algorithms · Computer Science 2022-05-31 Jason Li , Debmalya Panigrahi

Given a set $P$ of $n$ points in the plane, the unit-disk graph $G(P)$ is a graph with $P$ as its vertex set such that two points of $P$ have an edge if their Euclidean distance is at most $1$. We consider the problem of computing a maximum…

Computational Geometry · Computer Science 2025-06-30 Anastasiia Tkachenko , Haitao Wang

The theory of dense graph limits comes with a natural sampling process which yields an inhomogeneous variant G(n,W) of the Erdos-Renyi random graph. Here we study the clique number of these random graphs. We establish the concentration of…

Combinatorics · Mathematics 2018-12-04 Martin Doležal , Jan Hladký , András Máthé

There has recently been much progress on exact algorithms for the (un)weighted graph (bi)partitioning problem using branch-and-bound and related methods. In this note we present and improve an easily computable, purely combinatorial lower…

Data Structures and Algorithms · Computer Science 2014-10-03 Jesper Larsson Träff , Martin Wimmer

Finding the largest clique is a notoriously hard problem, even on random graphs. It is known that the clique number of a random graph G(n,1/2) is almost surely either k or k+1, where k = 2log n - 2log(log n) - 1. However, a simple greedy…

Data Structures and Algorithms · Computer Science 2008-09-22 Atish Das Sarma , Amit Deshpande , Ravi Kannan

We show that deciding whether a given graph $G$ of size $m$ has a unique perfect matching as well as finding that matching, if it exists, can be done in time $O(m)$ if $G$ is either a cograph, or a split graph, or an interval graph, or…

Combinatorics · Mathematics 2017-12-13 S. Chaplick , M. Fürst , F. Maffray , D. Rautenbach

Let ${\cal G}=(G,w)$ be a weighted simple finite connected graph, that is, let $G$ be a simple finite connected graph endowed with a function $w$ from the set of the edges of $G$ to the set of real numbers. For any subgraph $G'$ of $G$, we…

Combinatorics · Mathematics 2014-12-18 Elena Rubei

In this paper, we study the maximum clique problem on hyperbolic random graphs. A hyperbolic random graph is a mathematical model for analyzing scale-free networks since it effectively explains the power-law degree distribution of…

Data Structures and Algorithms · Computer Science 2023-06-30 Eunjin Oh , Seunghyeok Oh

We study the maximum weight perfect $f$-factor problem on any general simple graph $G=(V,E,w)$ with positive integral edge weights $w$, and $n=|V|$, $m=|E|$. When we have a function $f:V\rightarrow \mathbb{N}_+$ on vertices, a perfect…

Data Structures and Algorithms · Computer Science 2020-03-18 Ran Duan , Haoqing He , Tianyi Zhang

In 1996, Karger [Kar96] gave a startling randomized algorithm that finds a minimum-cut in a (weighted) graph in time $O(m\log^3n)$ which he termed near-linear time meaning linear (in the size of the input) times a polylogarthmic factor. In…

Data Structures and Algorithms · Computer Science 2024-01-12 Monika Henzinger , Jason Li , Satish Rao , Di Wang

We present an algorithm that on input of an $n$-vertex $m$-edge weighted graph $G$ and a value $k$, produces an {\em incremental sparsifier} $\hat{G}$ with $n-1 + m/k$ edges, such that the condition number of $G$ with $\hat{G}$ is bounded…

Data Structures and Algorithms · Computer Science 2015-03-13 Ioannis Koutis , Gary L. Miller , Richard Peng

Given a weighted graph $G$ and an error parameter $\epsilon > 0$, the {\em graph sparsification} problem requires sampling edges in $G$ and giving the sampled edges appropriate weights to obtain a sparse graph $G_{\epsilon}$ (containing…

Data Structures and Algorithms · Computer Science 2010-04-26 Ramesh Hariharan , Debmalya Panigrahi

For each m>=1 and k>=2, we construct a graph G=(V,E) with \omega(G)=m such that max_{1\leq i\leq k} \omega(G[V_i])=m for arbitrary partition V=V_1\cup...\cup V_k, where \omega(G) is the clique number of G and G[V_i] is the induced subgraph…

Combinatorics · Mathematics 2008-04-26 Hao Pan , Li-Lu Zhao

In this paper, we present a new exact algorithm for counting perfect matchings, which relies on neither inclusion-exclusion principle nor tree-decompositions. For any bipartite graph of $2n$ nodes and $\Delta n$ edges such that $\Delta \geq…

Data Structures and Algorithms · Computer Science 2012-08-14 Taisuke Izumi , Tadashi Wadayama