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We analyze a new spectral graph matching algorithm, GRAph Matching by Pairwise eigen-Alignments (GRAMPA), for recovering the latent vertex correspondence between two unlabeled, edge-correlated weighted graphs. Extending the exact recovery…

Probability · Mathematics 2019-07-23 Zhou Fan , Cheng Mao , Yihong Wu , Jiaming Xu

Graph matching, also known as network alignment, refers to finding a bijection between the vertex sets of two given graphs so as to maximally align their edges. This fundamental computational problem arises frequently in multiple fields…

Data Structures and Algorithms · Computer Science 2021-08-10 Cheng Mao , Mark Rudelson , Konstantin Tikhomirov

Random graph matching refers to recovering the underlying vertex correspondence between two random graphs with correlated edges; a prominent example is when the two random graphs are given by Erd\H{o}s-R\'{e}nyi graphs $G(n,\frac{d}{n})$.…

Machine Learning · Statistics 2020-07-21 Jian Ding , Zongming Ma , Yihong Wu , Jiaming Xu

This paper studies the problem of recovering the hidden vertex correspondence between two edge-correlated random graphs. We focus on the Gaussian model where the two graphs are complete graphs with correlated Gaussian weights and the…

Statistics Theory · Mathematics 2022-02-17 Yihong Wu , Jiaming Xu , Sophie H. Yu

Graph matching aims at finding the vertex correspondence between two unlabeled graphs that maximizes the total edge weight correlation. This amounts to solving a computationally intractable quadratic assignment problem. In this paper we…

Machine Learning · Statistics 2019-07-23 Zhou Fan , Cheng Mao , Yihong Wu , Jiaming Xu

This paper deals with the problem of graph matching or network alignment for Erd\H{o}s--R\'enyi graphs, which can be viewed as a noisy average-case version of the graph isomorphism problem. Let $G$ and $G'$ be $G(n, p)$ Erd\H{o}s--R\'enyi…

Statistics Theory · Mathematics 2022-07-08 Cheng Mao , Mark Rudelson , Konstantin Tikhomirov

Motivated by the problem of matching two correlated random geometric graphs, we study the problem of matching two Gaussian geometric models correlated through a latent node permutation. Specifically, given an unknown permutation $\pi^*$ on…

Statistics Theory · Mathematics 2026-04-08 Shuyang Gong , Zhangsong Li

This paper studies the problem of recovering a hidden vertex correspondence between two correlated graphs when both edge weights and node features are observed. While most existing work on graph alignment relies primarily on edge…

Statistics Theory · Mathematics 2026-04-07 Dong Huang , Chenyang Tian , Pengkun Yang

We study the problem of recovering a planted matching in randomly weighted complete bipartite graphs $K_{n,n}$. For some unknown perfect matching $M^*$, the weight of an edge is drawn from one distribution $P$ if $e \in M^*$ and another…

Data Structures and Algorithms · Computer Science 2020-11-11 Mehrdad Moharrami , Cristopher Moore , Jiaming Xu

In this paper, the problem of matching pairs of correlated random graphs with multi-valued edge attributes is considered. Graph matching problems of this nature arise in several settings of practical interest including social network…

Information Theory · Computer Science 2018-02-06 F. Shirani , S. Garg , E. Erkip

We consider the problem of finding edges of a hidden weighted graph using a certain type of queries. Let $G$ be a weighted graph with $n$ vertices. In the most general setting, the $n$ vertices are known and no other information about $G$…

Combinatorics · Mathematics 2012-01-19 Jeong Han Kim

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 paper introduces the \emph{$d$-distance matching problem}, in which we are given a bipartite graph $G=(S,T;E)$ with $S=\{s_1,\dots,s_n\}$, a weight function on the edges and an integer $d\in\mathbb Z_+$. The goal is to find a maximum…

Combinatorics · Mathematics 2023-01-24 Péter Madarasi

We study the graph matching problem in the presence of vertex feature information using shallow graph neural networks. Specifically, given two graphs that are independent perturbations of a single random geometric graph with sparse binary…

Machine Learning · Computer Science 2025-03-12 Suqi Liu , Morgane Austern

Random graphs with latent geometric structure are popular models of social and biological networks, with applications ranging from network user profiling to circuit design. These graphs are also of purely theoretical interest within…

Probability · Mathematics 2020-08-04 Matthew Brennan , Guy Bresler , Dheeraj Nagaraj

In this paper, we study the task of detecting the edge dependency between two weighted random graphs. We formulate this task as a simple hypothesis testing problem, where under the null hypothesis, the two observed graphs are statistically…

Machine Learning · Computer Science 2024-09-25 Mor Oren , Vered Paslev , Wasim Huleihel

Consider the random process in which the edges of a graph $G$ are added one by one in a random order. A classical result states that if $G$ is the complete graph $K_{2n}$ or the complete bipartite graph $K_{n,n}$, then typically a perfect…

Combinatorics · Mathematics 2020-11-03 Roman Glebov , Zur Luria , Michael Simkin

We equip the edges of a deterministic graph $H$ with independent but not necessarily identically distributed weights and study a generalized version of matchings (i.e. a set of vertex disjoint edges) in $H$ satisfying the property that…

Probability · Mathematics 2021-08-18 Ghurumuruhan Ganesan

We consider the problem of exact and inexact matching of weighted undirected graphs, in which a bijective correspondence is sought to minimize a quadratic weight disagreement. This computationally challenging problem is often relaxed as a…

Data Structures and Algorithms · Computer Science 2014-10-14 Yonathan Aflalo , Alex Bronstein , Ron Kimmel

Graph alignment refers to the task of finding the vertex correspondence between two correlated graphs of $n$ vertices. Extensive study has been done on polynomial-time algorithms for the graph alignment problem under the Erd\H{o}s-R\'enyi…

Data Structures and Algorithms · Computer Science 2024-06-12 Ziao Wang , Weina Wang , Lele Wang
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