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In a simple connected graph $G=(V,E)$, a subset of vertices $S \subseteq V$ is a dominating set if any vertex $v \in V\setminus S$ is adjacent to some vertex $x$ from this subset. A number of real-life problems can be modeled using this…

Data Structures and Algorithms · Computer Science 2023-09-04 Ernesto Parra Inza , Frank Angel Hernández Mira , José María Sigarreta Almira , Nodari Vakhania

Flexible network design deals with building a network that guarantees some connectivity requirements between its vertices, even when some of its elements (like vertices or edges) fail. In particular, the set of edges (resp. vertices) of a…

Data Structures and Algorithms · Computer Science 2024-04-16 Dylan Hyatt-Denesik , Afrouz Jabal Ameli , Laura Sanita

Given a graph, the minimum dominating set (MinDS) problem is to identify a smallest set $D$ of vertices such that every vertex not in $D$ is adjacent to at least one vertex in $D$. The MinDS problem is a classic $\mathcal{NP}$-hard problem…

Social and Information Networks · Computer Science 2023-08-01 Enqiang Zhu , Yu Zhang , Shengzhi Wang , Darren Strash , Chanjuan Liu

Given an undirected graph, $G$, and vertices, $s$ and $t$ in $G$, the tracking paths problem is that of finding the smallest subset of vertices in $G$ whose intersection with any $s$-$t$ path results in a unique sequence. This problem is…

Data Structures and Algorithms · Computer Science 2021-04-27 Michael T. Goodrich , Siddharth Gupta , Hadi Khodabandeh , Pedro Matias

A graph $G$ is called B$_k$-VPG (resp., B$_k$-EPG), for some constant $k\geq 0$, if it has a string representation on a grid such that each vertex is an orthogonal path with at most $k$ bends and two vertices are adjacent in $G$ if and only…

Computational Geometry · Computer Science 2017-02-21 Saeed Mehrabi

We consider the minimum weight and smallest weight minimum-size dominating set problems in vertex-weighted graphs and networks. The latter problem is a two-objective optimization problem, which is different from the classic minimum weight…

Combinatorics · Mathematics 2024-01-23 Lukas Dijkstra , Andrei Gagarin , Vadim Zverovich

We develop a new framework for generalizing approximation algorithms from the structural graph algorithm literature so that they apply to graphs somewhat close to that class (a scenario we expect is common when working with real-world…

In this paper, we propose a deterministic algorithm that approximates the optimal path cover on weighted undirected graphs. Based on the 1/2-Approximation Path Cover Algorithm by Moran et al., we add a procedure to remove the redundant…

Numerical Analysis · Mathematics 2021-01-25 Junyuan Lin , Guangpeng Ren

In this paper, we introduce the problem of Matroid-Constrained Vertex Cover: given a graph with weights on the edges and a matroid imposed on the vertices, our problem is to choose a subset of vertices that is independent in the matroid,…

Data Structures and Algorithms · Computer Science 2023-06-08 Chien-Chung Huang , François Sellier

This paper proposes a novel branch-and-bound(BMWVC) algorithm to exactly solve the minimum weight vertex cover problem (MWVC) in large graphs. The original contribution is several new graph reduction rules, allowing to reduce a graph G and…

Data Structures and Algorithms · Computer Science 2019-03-15 Luzhi Wang , Chu-Min Li , Junping Zhou , Bo Jin , Minghao Yin

We study the complexity of approximating the vertex expansion of graphs $G = (V,E)$, defined as \[ \Phi^V := \min_{S \subset V} n \cdot \frac{|N(S)|}{|S| |V \backslash S|}. \] We give a simple polynomial-time algorithm for finding a subset…

Computational Complexity · Computer Science 2013-11-12 Anand Louis , Prasad Raghavendra , Santosh Vempala

As graphs continue to grow in size, we seek ways to effectively process such data at scale. The model of streaming graph processing, in which a compact summary is maintained as each edge insertion/deletion is observed, is an attractive one.…

Data Structures and Algorithms · Computer Science 2014-07-25 Rajesh Chitnis , Graham Cormode , MohammadTaghi Hajiaghayi , Morteza Monemizadeh

Graph matching can be formalized as a combinatorial optimization problem, where there are corresponding relationships between pairs of nodes that can be represented as edges. This problem becomes challenging when there are potential…

Computer Vision and Pattern Recognition · Computer Science 2023-01-06 Dongdong Chen , Yuxing Dai , Lichi Zhang , Zhihong Zhang

Massive Multiple-Input Multiple-Out (MIMO) detection is an important problem in modern wireless communication systems. While traditional Belief Propagation (BP) detectors perform poorly on loopy graphs, the recent Graph Neural Networks…

Information Theory · Computer Science 2022-06-15 Hongyi Li , Junxiang Wang , Yongchao Wang

The power dominating set (PDS) problem is the following extension of the well-known dominating set problem: find a smallest-size set of nodes $S$ that power dominates all the nodes, where a node $v$ is power dominated if (1) $v$ is in $S$…

Computational Complexity · Computer Science 2007-10-12 Ashkan Aazami , Michael D. Stilp

Graph similarity computation is one of the core operations in many graph-based applications, such as graph similarity search, graph database analysis, graph clustering, etc. Since computing the exact distance/similarity between two graphs…

Machine Learning · Computer Science 2021-05-18 Yunsheng Bai , Hao Ding , Yizhou Sun , Wei Wang

Graph Crossing Number is a fundamental problem with various applications. In this problem, the goal is to draw an input graph $G$ in the plane so as to minimize the number of crossings between the images of its edges. Despite extensive…

Data Structures and Algorithms · Computer Science 2021-01-12 Julia Chuzhoy , Sepideh Mahabadi , Zihan Tan

Let G=(V,E) be a graph. A vertex dominates itself and all its neighbors, i.e., every vertex v in V dominates its closed neighborhood N[v]. A vertex set D in G is an efficient dominating (e.d.) set for G if for every vertex v in V, there is…

Discrete Mathematics · Computer Science 2012-07-09 Andreas Brandstädt , Arne Leitert , Dieter Rautenbach

We design improved approximation algorithms for NP-hard graph problems by incorporating predictions (e.g., learned from past data). Our prediction model builds upon and extends the $\varepsilon$-prediction framework by Cohen-Addad, d'Orsi,…

Machine Learning · Computer Science 2025-06-02 Anders Aamand , Justin Y. Chen , Siddharth Gollapudi , Sandeep Silwal , Hao Wu

Given a graph, the shortest-path problem requires finding a sequence of edges with minimum cumulative length that connects a source vertex to a target vertex. We consider a variant of this classical problem in which the position of each…

Discrete Mathematics · Computer Science 2024-05-10 Tobia Marcucci , Jack Umenberger , Pablo A. Parrilo , Russ Tedrake