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We study a well known noisy model of the graph isomorphism problem. In this model, the goal is to perfectly recover the vertex correspondence between two edge-correlated Erd\H{o}s-R\'{e}nyi random graphs, with an initial seed set of…

Machine Learning · Computer Science 2018-07-27 Elchanan Mossel , Jiaming Xu

Let $X_1,X_2,...$ be an infinite sequence of i.i.d. random vectors distributed exponentially with parameter $\lam .$ For each $y$ and $n\geq 1,$ form a graph $G_n(y)$ with vertex set $V_n = \{X_1,...,X_n\},$ two vertices are connected if…

Probability · Mathematics 2007-05-23 Bhupendra Gupta

We establish the asymptotic degree distribution of the typical vertex of inhomogeneous and passive random intersection graphs under the minimal moment conditions.

Probability · Mathematics 2019-08-26 Mindaugas Bloznelis

Graph matching---aligning a pair of graphs to minimize their edge disagreements---has received wide-spread attention from both theoretical and applied communities over the past several decades, including combinatorics, computer vision, and…

We present a simple nonadaptive randomized algorithm that estimates the number of edges in a simple, unweighted, undirected graph, possibly containing isolated vertices, using only degree and random edge queries. For an $n$-vertex graph,…

Data Structures and Algorithms · Computer Science 2025-12-16 Arijit Bishnu , Debarshi Chanda , Buddha Dev Das , Arijit Ghosh , Gopinath Mishra

We propose a simple and efficient local algorithm for graph isomorphism which succeeds for a large class of sparse graphs. This algorithm produces a low-depth canonical labeling, which is a labeling of the vertices of the graph that…

Probability · Mathematics 2023-09-20 Julia Gaudio , Miklós Z. Rácz , Anirudh Sridhar

Cohesive subgraph discovery in a network is one of the fundamental problems and investigated for several decades. In this paper, we propose the Overlapping Cohesive Subgraphs with Minimum degree (OCSM) problem which combines three key…

Social and Information Networks · Computer Science 2022-06-13 Junghoon Kim , Sungsu Lim , Jungeun Kim

This thesis studies the graph alignment problem, the noisy version of the graph isomorphism problem, which aims to find a matching between the nodes of two graphs which preserves most of the edges. Focusing on the planted version where the…

Data Structures and Algorithms · Computer Science 2024-04-22 Luca Ganassali

Graph matching is a fruitful area in terms of both algorithms and theories. In this paper, we exploit the degree information, which was previously used only in noiseless graphs and perfectly-overlapping Erd\H{o}s--R\'enyi random graphs…

Methodology · Statistics 2020-06-08 Yaofang Hu , Wanjie Wang , Yi Yu

The paper presents an algorithm for minimum vertex cover problem, which is an NP-Complete problem. The algorithm computes a minimum vertex cover of each input simple graph. Tested by the attached MATLAB programs, Stage 1 of the algorithm is…

Discrete Mathematics · Computer Science 2016-10-30 Gang Hu

Given two Erd\H{o}s-R\'enyi graphs with $n$ vertices whose edges are correlated through a latent vertex correspondence, we study complexity lower bounds for the associated correlation detection problem for the class of low-degree polynomial…

Data Structures and Algorithms · Computer Science 2025-11-11 Jian Ding , Hang Du , Zhangsong Li

In this paper we consider alignment of sparse graphs, for which we introduce the Neighborhood Tree Matching Algorithm (NTMA). For correlated Erd\H{o}s-R\'{e}nyi random graphs, we prove that the algorithm returns -- in polynomial time -- a…

Data Structures and Algorithms · Computer Science 2020-11-02 Luca Ganassali , Laurent Massoulié

This paper studies the problem of matching two complete graphs with edge weights correlated through latent geometries, extending a recent line of research on random graph matching with independent edge weights to geometric models.…

Statistics Theory · Mathematics 2022-02-25 Haoyu Wang , Yihong Wu , Jiaming Xu , Israel Yolou

Existence of a perfect matching in a random bipartite digraph with bipartition $(V_1, V_2)$, $|V_i|=n$, is studied. The graph is generated in two rounds of random selections of a potential matching partner such that the average number of…

Combinatorics · Mathematics 2019-03-15 Michal Karoński , Ed Overman , Boris Pittel

We consider the following stochastic optimization problem first introduced by Chen et al. in \cite{chen}. We are given a vertex set of a random graph where each possible edge is present with probability p_e. We do not know which edges are…

Data Structures and Algorithms · Computer Science 2015-03-20 Kevin Costello , Prasad Tetali , Pushkar Tripathi

Finding optimal matchings in dense graphs is of general interest and of particular importance in social, transportation and biological networks. While developing optimal solutions for various matching problems is important, the running…

Data Structures and Algorithms · Computer Science 2020-11-16 Nitish K. Panigrahy , Prithwish Basu , Don Towsley

We propose a model for online graph problems where algorithms are given access to an oracle that predicts (e.g., based on modeling assumptions or on past data) the degrees of nodes in the graph. Within this model, we study the classic…

Data Structures and Algorithms · Computer Science 2022-11-16 Anders Aamand , Justin Y. Chen , Piotr Indyk

The problem of learning a correspondence relationship between nodes of two networks has drawn much attention of the computer science community and recently that of statisticians. The unseeded version of this problem, in which we do not know…

Methodology · Statistics 2018-08-24 Yuan Zhang

It is well-known that every $n$-vertex planar graph with minimum degree 3 has a matching of size at least $\frac{n}{3}$. But all proofs of this use the Tutte-Berge-formula for the size of a maximum matching. Hence these proofs are not…

Data Structures and Algorithms · Computer Science 2019-02-22 Therese Biedl

We formulate and analyze a heterogeneous random hypergraph model, and we provide an achieveability result for recovery of hyperedges from the observed projected graph. We observe a projected graph which combines random hyperedges across all…

Data Structures and Algorithms · Computer Science 2026-03-03 Alexander Morgan , Chenghao Guo