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The number of triangles in a graph is useful to deduce a plethora of important features of the network that the graph is modeling. However, finding the exact value of this number is computationally expensive. Hence, a number of…

Data Structures and Algorithms · Computer Science 2017-10-30 Duru Türkoğlu , Ata Turk

The widely studied edge modification problems ask how to minimally alter a graph to satisfy certain structural properties. In this paper, we introduce and study a new edge modification problem centered around transforming a given graph into…

Data Structures and Algorithms · Computer Science 2025-09-16 Amirali Madani , Anil Maheshwari , Babak Miraftab , Paweł Żyliński

We consider the problem of sampling an edge almost uniformly from an unknown graph, $G = (V, E)$. Access to the graph is provided via queries of the following types: (1) uniform vertex queries, (2) degree queries, and (3) neighbor queries.…

Computational Complexity · Computer Science 2017-06-30 Talya Eden , Will Rosenbaum

Proximity graph-based methods have emerged as a leading paradigm for approximate nearest neighbor (ANN) search in the system community. This paper presents fresh insights into the theoretical foundation of these methods. We describe an…

Data Structures and Algorithms · Computer Science 2025-09-10 Shangqi Lu , Yufei Tao

We study the arboricity A and the maximum number T of edge-disjoint spanning trees of the Erdos-Renyi random graph G(n,p). For all p(n) in [0,1], we show that, with high probability, T is precisely the minimum between delta and…

Combinatorics · Mathematics 2014-05-29 Pu Gao , Xavier Pérez-Giménez , Cristiane M. Sato

Given query access to an undirected graph $G$, we consider the problem of computing a $(1\pm\epsilon)$-approximation of the number of $k$-cliques in $G$. The standard query model for general graphs allows for degree queries, neighbor…

Data Structures and Algorithms · Computer Science 2018-11-13 Talya Eden , Dana Ron , C. Seshadhri

We show an $\widetilde{O}(m^{1.5} \epsilon^{-1})$ time algorithm that on a graph with $m$ edges and $n$ vertices outputs its spanning tree count up to a multiplicative $(1+\epsilon)$ factor with high probability, improving on the previous…

Data Structures and Algorithms · Computer Science 2025-05-21 Yang P. Liu , Richard Peng , Junzhao Yang

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

Let $G$ be an $n$-vertex graph with $m$ edges. When asked a subset $S$ of vertices, a cut query on $G$ returns the number of edges of $G$ that have exactly one endpoint in $S$. We show that there is a bounded-error quantum algorithm that…

Data Structures and Algorithms · Computer Science 2020-08-05 Troy Lee , Miklos Santha , Shengyu Zhang

Let $N_{\triangle}(G)$ be the number of triangles in a graph $G$. In [14] and [25] (respectively) the following bounds were proved on the lower tail behaviour of triangle counts in the dense Erd\H{o}s-R\'enyi random graphs $G_m\sim G(n,m)$:…

Combinatorics · Mathematics 2025-11-03 José Alvarado , Gabriel Dias , Simon Griffiths

Estimating the number of triangles in a graph is one of the most fundamental problems in sublinear algorithms. In this work, we provide an algorithm that approximately counts the number of triangles in a graph using only polylogarithmic…

Data Structures and Algorithms · Computer Science 2020-08-04 Anup Bhattacharya , Arijit Bishnu , Arijit Ghosh , Gopinath Mishra

We consider the problem of finding an edge in a hidden undirected graph $G = (V, E)$ with $n$ vertices, in a model where we only allowed queries that ask whether or not a subset of vertices contains an edge. We study the non-adaptive model…

Data Structures and Algorithms · Computer Science 2022-07-07 Ron Kupfer , Noam Nisan

We study the problem of estimating the number of triangles in a graph stream. No streaming algorithm can get sublinear space on all graphs, so methods in this area bound the space in terms of parameters of the input graph such as the…

Data Structures and Algorithms · Computer Science 2019-04-18 John Kallaugher , Eric Price

We prove that the treewidth of an Erd\"{o}s-R\'{e}nyi random graph $\rg{n, m}$ is, with high probability, greater than $\beta n$ for some constant $\beta > 0$ if the edge/vertex ratio $\frac{m}{n}$ is greater than 1.073. Our lower bound…

Discrete Mathematics · Computer Science 2009-08-03 Yong Gao

In this work, we estimate the number of hyperedges in a hypergraph ${\cal H}(U({\cal H}), {\cal F}({\cal H}))$, where $U({\cal H})$ denotes the set of vertices and ${\cal F}({\cal H}))$ denotes the set of hyperedges. We assume a query…

Data Structures and Algorithms · Computer Science 2020-09-08 Anup Bhattacharya , Arijit Bishnu , Arijit Ghosh , Gopinath Mishra

We study the problem of estimating the number of edges in an unknown graph. We consider a hybrid model in which an algorithm may issue independent set, degree, and neighbor queries. We show that this model admits strictly more efficient…

Data Structures and Algorithms · Computer Science 2026-01-30 Tomer Adar , Yahel Hotam , Amit Levi

The area of sublinear algorithms have recently received a lot of attention. In this setting, one has to choose specific access model for the input, as the algorithm does not have time to pre-process or even to see the whole input. A…

Data Structures and Algorithms · Computer Science 2020-09-24 Jakub Tětek

We revisit the well-studied problem of triangle count estimation in graph streams. Given a graph represented as a stream of $m$ edges, our aim is to compute a $(1\pm\varepsilon)$-approximation to the triangle count $T$, using a small space…

Data Structures and Algorithms · Computer Science 2020-03-31 Suman K. Bera , C. Seshadhri

We consider a weighted counting problem on matchings, denoted $\textrm{PrMatching}(\mathcal{G})$, on an arbitrary fixed graph family $\mathcal{G}$. The input consists of a graph $G\in \mathcal{G}$ and of rational probabilities of existence…

Computational Complexity · Computer Science 2023-01-10 Antoine Amarilli , Mikaël Monet

We study the inference of network archaeology in growing random geometric graphs. We consider the root finding problem for a random nearest neighbor tree in dimension $d \in \mathbb{N}$, generated by sequentially embedding vertices…

Probability · Mathematics 2024-11-22 Anna Brandenberger , Cassandra Marcussen , Elchanan Mossel , Madhu Sudan