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In a large-scale network, we want to choose some influential nodes to make a profit by paying some cost within a limited budget so that we do not have to spend more budget on some nodes adjacent to the chosen nodes; our problem is the…

Data Structures and Algorithms · Computer Science 2026-01-30 Sipra Singh

The classic lower bound of Kuhn, Moscibroda and Wattenhofer [JACM 2016] states that approximate maximum matching and approximate vertex cover (among other problems) in the LOCAL model require $\Omega(\min\{\sqrt{\frac{\log n}{\log\log n}},…

Data Structures and Algorithms · Computer Science 2026-05-14 Peter Davies-Peck

We describe a distributed randomized algorithm computing approximate distances and routes that approximate shortest paths. Let n denote the number of nodes in the graph, and let HD denote the hop diameter of the graph, i.e., the diameter of…

Distributed, Parallel, and Cluster Computing · Computer Science 2012-11-05 Christoph Lenzen , Boaz Patt-Shamir

A self-stabilizing algorithm for the minimal $\alpha$-dominating set is proposed in this paper. The $\alpha$-domination parameter has not used before in self-stabilization paradigm. Using an arbitrary graph with $n$ nodes and $m$ edges, the…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-06-03 Badreddine Benreguia , Hamouma Moumen

We consider the problem of maintaining an approximately maximum (fractional) matching and an approximately minimum vertex cover in a dynamic graph. Starting with the seminal paper by Onak and Rubinfeld [STOC 2010], this problem has received…

Data Structures and Algorithms · Computer Science 2017-04-11 Sayan Bhattacharya , Monika Henzinger , Danupon Nanongkai

In this paper, we revisit the classic approximate All-Pairs Shortest Paths (APSP) problem in undirected graphs. For unweighted graphs, we provide an algorithm for $2$-approximate APSP in $\tilde O(n^{2.5-r}+n^{\omega(r)})$ time, for any…

Data Structures and Algorithms · Computer Science 2023-10-31 Michal Dory , Sebastian Forster , Yael Kirkpatrick , Yasamin Nazari , Virginia Vassilevska Williams , Tijn de Vos

Conditional lower bounds for dynamic graph problems has received a great deal of attention in recent years. While many results are now known for the fully-dynamic case and such bounds often imply worst-case bounds for the partially dynamic…

Data Structures and Algorithms · Computer Science 2016-05-04 Søren Dahlgaard

We provide an algorithm that maintains, against an adaptive adversary, a $(1-\varepsilon)$-approximate maximum matching in $n$-node $m$-edge general (not necessarily bipartite) undirected graph undergoing edge deletions with high…

Data Structures and Algorithms · Computer Science 2024-12-05 Jiale Chen , Aaron Sidford , Ta-Wei Tu

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

A dominating set $D$ of a graph $G$ is a set of vertices such that any vertex in $G$ is in $D$ or its neighbor is in $D$. Enumeration of minimal dominating sets in a graph is one of central problems in enumeration study since enumeration of…

Data Structures and Algorithms · Computer Science 2020-09-23 Kazuhiro Kurita , Kunihiro Wasa , Hiroki Arimura , Takeaki Uno

The Max-Cut problem is a well known combinatorial optimization problem. In this paper we describe a fast approximation method. Given a graph G, we want to find a cut whose size is maximal among all possible cuts. A cut is a partition of the…

Analysis of PDEs · Mathematics 2019-07-11 Blaine Keetch , Yves van Gennip

We present a new approach to randomized distributed graph coloring that is simpler and more efficient than previous ones. In particular, it allows us to tackle the $(\operatorname{deg}+1)$-list-coloring (D1LC) problem, where each node $v$…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-12-02 Magnús M. Halldórsson , Fabian Kuhn , Alexandre Nolin , Tigran Tonoyan

Diffusion is a fundamental graph procedure and has been a basic building block in a wide range of theoretical and empirical applications such as graph partitioning and semi-supervised learning on graphs. In this paper, we study…

Data Structures and Algorithms · Computer Science 2021-06-07 Li Chen , Richard Peng , Di Wang

We consider the problem of finding a minimum edge cost subgraph of a graph satisfying both given node-connectivity requirements and degree upper bounds on nodes. We present an iterative rounding algorithm of the biset LP relaxation for this…

Data Structures and Algorithms · Computer Science 2015-08-11 Takuro Fukunaga , Zeev Nutov , R. Ravi

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

Given an unweighted graph $G$, the *minimum $r$-dominating set problem* asks for the smallest-cardinality subset $S$ such that every vertex in $G$ is within radius $r$ of some vertex in $S$. While the $r$-dominating set problem on planar…

Data Structures and Algorithms · Computer Science 2026-04-02 Reilly Browne , Hsien-Chih Chang

The Matching Augmentation Problem (MAP) has recently received significant attention as an important step towards better approximation algorithms for finding cheap $2$-edge connected subgraphs. This has culminated in a…

Data Structures and Algorithms · Computer Science 2022-08-25 Etienne Bamas , Marina Drygala , Ola Svensson

Many problems in real life can be converted to combinatorial optimization problems (COPs) on graphs, that is to find a best node state configuration or a network structure such that the designed objective function is optimized under some…

Machine Learning · Computer Science 2019-09-17 Jing Liu , Fei Gao , Jiang Zhang

In the decremental single-source shortest paths (SSSP) problem, the input is an undirected graph $G=(V,E)$ with $n$ vertices and $m$ edges undergoing edge deletions, together with a fixed source vertex $s\in V$. The goal is to maintain a…

Data Structures and Algorithms · Computer Science 2020-09-21 Julia Chuzhoy , Thatchaphol Saranurak

Orienteering is the following optimization problem: given an edge-weighted graph (directed or undirected), two nodes s,t and a time limit T, find an s-t walk of total length at most T that maximizes the number of distinct nodes visited by…

Data Structures and Algorithms · Computer Science 2007-12-03 Chandra Chekuri , Nitish Korula