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We give an efficient algorithm to generate a graph from a distribution $\epsilon$-close to $G(n,p)$, in the sense of total variation distance. In particular, if $p$ is represented with $O(\log n)$-bit accuracy, then, with high probability,…

Data Structures and Algorithms · Computer Science 2012-07-13 Antonio Blanca , Milena Mihail

We study the problem of robustly estimating the parameter $p$ of an Erd\H{o}s-R\'enyi random graph on $n$ nodes, where a $\gamma$ fraction of nodes may be adversarially corrupted. After showing the deficiencies of canonical estimators, we…

Data Structures and Algorithms · Computer Science 2022-02-16 Jayadev Acharya , Ayush Jain , Gautam Kamath , Ananda Theertha Suresh , Huanyu Zhang

What is the probability that the number of triangles in $\mathcal{G}_{n,p}$, the Erd\H{o}s-R\'enyi random graph with edge density $p$, is at least twice its mean? Writing it as $\exp[- r(n,p)]$, already the order of the rate function…

Combinatorics · Mathematics 2019-04-12 Eyal Lubetzky , Yufei Zhao

In dense Erd\H{o}s-R\'enyi random graphs, we are interested in the events where large numbers of a given subgraph occur. The mean behavior of subgraph counts is known, and only recently were the related large deviations results discovered.…

Probability · Mathematics 2014-04-03 Shankar Bhamidi , Jan Hannig , Chia Ying Lee , James Nolen

For a graph $G$ and $p\in[0,1]$, we denote by $G_p$ the random sparsification of $G$ obtained by keeping each edge of $G$ independently, with probability $p$. We show that there exists a $C>0$ such that if $p\geq C(\log n)^{1/3}n^{-2/3}$…

We consider the near-critical Erd\H{o}s-R\'{e}nyi random graph $G(n,p)$ and provide a new probabilistic proof of the fact that, when $p$ is of the form $p=p(n)=1/n+\lambda/n^{4/3}$ and $A$ is large,…

Probability · Mathematics 2021-01-15 Umberto De Ambroggio , Matthew I. Roberts

In this paper, we revisit the problem of sampling edges in an unknown graph $G = (V, E)$ from a distribution that is (pointwise) almost uniform over $E$. We consider the case where there is some a priori upper bound on the arboriciy of $G$.…

Computational Complexity · Computer Science 2019-02-22 Talya Eden , Dana Ron , Will Rosenbaum

We consider the following stochastic matching problem on both weighted and unweighted graphs: A graph $G(V, E)$ along with a parameter $p \in (0, 1)$ is given in the input. Each edge of $G$ is realized independently with probability $p$.…

Data Structures and Algorithms · Computer Science 2018-11-09 Soheil Behnezhad , Alireza Farhadi , MohammadTaghi Hajiaghayi , Nima Reyhani

In this paper we consider the problem of embedding almost-spanning, bounded degree graphs in a random graph. In particular, let $\Delta\geq 5$, $\varepsilon > 0$ and let $H$ be a graph on $(1-\varepsilon)n$ vertices and with maximum degree…

Combinatorics · Mathematics 2017-08-04 Asaf Ferber , Kyle Luh , Oanh Nguyen

The number of triangles is a computationally expensive graph statistic which is frequently used in complex network analysis (e.g., transitivity ratio), in various random graph models (e.g., exponential random graph model) and in important…

Data Structures and Algorithms · Computer Science 2015-05-20 Mihail N. Kolountzakis , Gary L. Miller , Richard Peng , Charalampos E. Tsourakakis

The following question is due to Chatterjee and Varadhan (2011). Fix $0<p<r<1$ and take $G\sim G(n,p)$, the Erd\H{o}s-R\'enyi random graph with edge density $p$, conditioned to have at least as many triangles as the typical $G(n,r)$. Is $G$…

Probability · Mathematics 2016-02-05 Eyal Lubetzky , Yufei Zhao

Learning properties of large graphs from samples has been an important problem in statistical network analysis since the early work of Goodman \cite{Goodman1949} and Frank \cite{Frank1978}. We revisit a problem formulated by Frank…

Statistics Theory · Mathematics 2019-06-18 Jason M. Klusowski , Yihong Wu

We investigate in this paper the estimation of Gaussian graphs by model selection from a non-asymptotic point of view. We start from a n-sample of a Gaussian law P_C in R^p and focus on the disadvantageous case where n is smaller than p. To…

Statistics Theory · Mathematics 2008-07-16 Christophe Giraud

We study the two inference problems of detecting and recovering an isolated community of \emph{general} structure planted in a random graph. The detection problem is formalized as a hypothesis testing problem, where under the null…

Data Structures and Algorithms · Computer Science 2022-01-25 Wasim Huleihel

Triangle counting in hypergraph streams, including both hyper-vertex and hyper-edge triangles, is a fundamental problem in hypergraph analytics, with broad applications. However, existing methods face two key limitations: (i) an incomplete…

Data Structures and Algorithms · Computer Science 2025-09-03 Lingkai Meng , Long Yuan , Xuemin Lin , Wenjie Zhang , Ying Zhang

In this study, we investigate the problem of classifying, characterizing, and designing efficient algorithms for hard inference problems on planar graphs, in the limit of infinite size. The problem is considered hard if, for a deterministic…

Statistics Theory · Mathematics 2016-01-01 Iuliana Teodorescu , Razvan Teodorescu , Pranav Warman

Triangle counting is an important problem in graph mining. Clustering coefficients of vertices and the transitivity ratio of the graph are two metrics often used in complex network analysis. Furthermore, triangles have been used…

Data Structures and Algorithms · Computer Science 2009-06-30 Charalampos E. Tsourakakis , Mihail N. Kolountzakis , Gary L. Miller

We study random subgraphs of an arbitrary finite connected transitive graph $\mathbb G$ obtained by independently deleting edges with probability $1-p$. Let $V$ be the number of vertices in $\mathbb G$, and let $\Omega$ be their degree. We…

Probability · Mathematics 2007-05-23 Christian Borgs , Jennifer T. Chayes , Remco van der Hofstad , Gordon Slade , Joel Spencer

We consider the robustness of computational hardness of problems whose input is obtained by applying independent random deletions to worst-case instances. For some classical $NP$-hard problems on graphs, such as Coloring, Vertex-Cover, and…

Computational Complexity · Computer Science 2015-08-11 Daniel Reichman , Igor Shinkar

Graphs are used to model interactions in a variety of contexts, and there is a growing need to quickly assess the structure of such graphs. Some of the most useful graph metrics are based on triangles, such as those measuring social…

Social and Information Networks · Computer Science 2014-10-21 C. Seshadhri , Ali Pinar , Tamara G. Kolda