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A local algorithm is a distributed algorithm that completes after a constant number of synchronous communication rounds. We present local approximation algorithms for the minimum dominating set problem and the maximum matching problem in…

Distributed, Parallel, and Cluster Computing · Computer Science 2010-02-02 Matti Åstrand , Valentin Polishchuk , Joel Rybicki , Jukka Suomela , Jara Uitto

The main goal in distributed symmetry-breaking is to understand the locality of problems; i.e., the radius of the neighborhood that a node needs to explore in order to arrive at its part of a global solution. In this work, we study the…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-10-23 Seri Khoury , Manish Purohit , Aaron Schild , Joshua Wang

We study distributed algorithms that find a maximal matching in an anonymous, edge-coloured graph. If the edges are properly coloured with $k$ colours, there is a trivial greedy algorithm that finds a maximal matching in $k-1$ synchronous…

Distributed, Parallel, and Cluster Computing · Computer Science 2013-12-24 Juho Hirvonen , Jukka Suomela

$ $We study the $d$-Uniform Hypergraph Matching ($d$-UHM) problem: given an $n$-vertex hypergraph $G$ where every hyperedge is of size $d$, find a maximum cardinality set of disjoint hyperedges. For $d\geq3$, the problem of finding the…

Data Structures and Algorithms · Computer Science 2020-09-22 Oussama Hanguir , Clifford Stein

Given a source of iid samples of edges of an input graph $G$ with $n$ vertices and $m$ edges, how many samples does one need to compute a constant factor approximation to the maximum matching size in $G$? Moreover, is it possible to obtain…

Data Structures and Algorithms · Computer Science 2019-07-15 Michael Kapralov , Slobodan Mitrović , Ashkan Norouzi-Fard , Jakab Tardos

Randomized greedy algorithms form one of the simplest yet most effective approaches for computing approximate matchings in graphs. In this paper, we focus on the class of vertex-iterative (VI) randomized greedy matching algorithms, which…

Data Structures and Algorithms · Computer Science 2026-04-02 Mahsa Derakhshan , Tao Yu

We find new upper bounds on the size of a minimum totally dominating set for random regular graphs and for regular graphs with large girth. These bounds are obtained through the analysis of a local algorithm using a method due to Hoppen and…

Combinatorics · Mathematics 2020-01-07 Carlos Hoppen , Giovane Mansan

Inspired by sequential budgeted allocation problems, we study the online matching problem with budget refills. In this context, we consider an online bipartite graph $G=(U,V,E)$, where the nodes in $V$ are discovered sequentially and nodes…

Data Structures and Algorithms · Computer Science 2025-07-08 Maria Cherifa , Clément Calauzènes , Vianney Perchet

A maximal $\varepsilon$-near perfect matching is a maximal matching which covers at least $(1-\varepsilon)|V(G)|$ vertices. In this paper, we study the number of maximal near perfect matchings in generalized quasirandom and dense graphs. We…

Combinatorics · Mathematics 2019-02-07 Yifan Jing , Akbar Rafiey

Understanding the power of space-bounded computation with access to catalytic space has been an important theme in complexity theory over the recent years. One of the key algorithmic results in this area is that bipartite maximum matching…

Computational Complexity · Computer Science 2026-04-28 Srijan Chakraborty , Samir Datta , Aryan Kusre , Partha Mukhopadhyay , Amit Sinhababu

A matching in a graph is uniquely restricted if no other matching covers exactly the same set of vertices. This notion was defined by Golumbic, Hirst, and Lewenstein and studied in a number of articles. Our contribution is twofold. We…

Combinatorics · Mathematics 2016-11-22 Julien Baste , Dieter Rautenbach , Ignasi Sau

Consider a random graph model where each possible edge $e$ is present independently with some probability $p_e$. Given these probabilities, we want to build a large/heavy matching in the randomly generated graph. However, the only way we…

Data Structures and Algorithms · Computer Science 2010-09-01 Nikhil Bansal , Anupam Gupta , Jian Li , Julian Mestre , Viswanath Nagarajan , Atri Rudra

This work studies fundamental limits for recovering the underlying correspondence among multiple correlated graphs. In the setting of inhomogeneous random graphs, we present and analyze a matching algorithm: first partially match the graphs…

Data Structures and Algorithms · Computer Science 2025-07-01 Taha Ameen , Bruce Hajek

Graph matching is an important problem in machine learning and pattern recognition. Herein, we present theoretical and practical results on the consistency of graph matching for estimating a latent alignment function between the vertex sets…

Optimization and Control · Mathematics 2014-08-04 Vince Lyzinski , Donniell E. Fishkind , Carey E. Priebe

In this paper, we consider a randomized greedy algorithm for independent sets in $r$-uniform $d$-regular hypergraphs $G$ on $n$ vertices with girth $g$. By analyzing the expected size of the independent sets generated by this algorithm, we…

Combinatorics · Mathematics 2022-01-06 Jiaxi Nie , Jacques Verstraete

As massive graphs become more prevalent, there is a rapidly growing need for scalable algorithms that solve classical graph problems, such as maximum matching and minimum vertex cover, on large datasets. For massive inputs, several…

Data Structures and Algorithms · Computer Science 2018-12-31 Sepehr Assadi , MohammadHossein Bateni , Aaron Bernstein , Vahab Mirrokni , Cliff Stein

Motivated by sequential budgeted allocation problems, we investigate online matching problems where connections between vertices are not i.i.d., but they have fixed degree distributions -- the so-called configuration model. We estimate the…

Data Structures and Algorithms · Computer Science 2021-07-05 Nathan Noiry , Flore Sentenac , Vianney Perchet

We present a novel approach for finding multiple noisily embedded template graphs in a very large background graph. Our method builds upon the graph-matching-matched-filter technique proposed in Sussman et al., with the discovery of…

Machine Learning · Statistics 2024-07-08 Zhirui Li , Ben Johnson , Daniel L. Sussman , Carey E. Priebe , Vince Lyzinski

Maximum weight matching is one of the most fundamental combinatorial optimization problems with a wide range of applications in data mining and bioinformatics. Developing distributed weighted matching algorithms is challenging due to the…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-06-06 Sepehr Assadi , MohammadHossein Bateni , Vahab Mirrokni

The random greedy algorithm for finding a maximal independent set in a graph constructs a maximal independent set by inspecting the graph's vertices in a random order, adding the current vertex to the independent set if it is not adjacent…

Combinatorics · Mathematics 2023-09-28 Michael Krivelevich , Tamás Mészáros , Peleg Michaeli , Clara Shikhelman