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Related papers: On Sampling Edges Almost Uniformly

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Triangle counting and sampling are two fundamental problems for streaming algorithms. Arguably, designing sampling algorithms is more challenging than their counting variants. It may be noted that triangle counting has received far greater…

Data Structures and Algorithms · Computer Science 2024-05-17 Arijit Bishnu , Arijit Ghosh , Gopinath Mishra , Sayantan Sen

In this work we provide a new technique to design fast approximation algorithms for graph problems where the points of the graph lie in a metric space. Specifically, we present a sampling approach for such metric graphs that, using a…

Data Structures and Algorithms · Computer Science 2018-07-26 Hossein Esfandiari , Michael Mitzenmacher

We study the problem of edge partitioning, where the goal is to partition the edge set of a graph into several parts. The replication factor of a vertex $v$ is the number of parts that contain edges incident to $v$. The goal is to minimize…

Discrete Mathematics · Computer Science 2026-05-08 Alexander Yakunin , Andrey Kupavskii , Alexander Sushin , Stanislav Moiseev

We consider the problem of learning a general graph $G=(V,E)$ using edge-detecting queries, where the number of vertices $|V|=n$ is given to the learner. The information theoretic lower bound gives $m\log n$ for the number of queries, where…

Machine Learning · Computer Science 2018-03-29 Hasan Abasi , Nader H. Bshouty

We present a new algorithm for approximating the number of triangles in a graph $G$ whose edges arrive as an arbitrary order stream. If $m$ is the number of edges in $G$, $T$ the number of triangles, $\Delta_E$ the maximum number of…

Data Structures and Algorithms · Computer Science 2021-07-16 Rajesh Jayaram , John Kallaugher

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

In this paper, we consider the problems from the area of sublinear-time algorithms of edge sampling, edge counting, and triangle counting. Part of our contribution is that we consider three different settings, differing in the way in which…

Data Structures and Algorithms · Computer Science 2022-04-13 Jakub Tětek , Mikkel Thorup

How efficiently can we find an unknown graph using distance or shortest path queries between its vertices? Let $G = (V,E)$ be an unweighted, connected graph of bounded degree. The edge set $E$ is initially unknown, and the graph can be…

Data Structures and Algorithms · Computer Science 2015-02-19 Sampath Kannan , Claire Mathieu , Hang Zhou

Finding important edges in a graph is a crucial problem for various research fields, such as network epidemics, signal processing, machine learning, and sensor networks. In this paper, we tackle the problem based on sampling theory on…

Signal Processing · Electrical Eng. & Systems 2024-07-16 Kenta Yanagiya , Koki Yamada , Yasuo Katsuhara , Tomoya Takatani , Yuichi Tanaka

A central theme in sublinear graph algorithms is the relationship between counting and sampling: can the ability to approximately count a combinatorial structure be leveraged to sample it nearly uniformly at essentially the same cost? We…

Data Structures and Algorithms · Computer Science 2026-03-18 Tomer Adar , Amit Levi

In the Network Inference problem, one seeks to recover the edges of an unknown graph from the observations of cascades propagating over this graph. In this paper, we approach this problem from the sparse recovery perspective. We introduce a…

Social and Information Networks · Computer Science 2024-11-14 Jean Pouget-Abadie , Thibaut Horel

We study a number of graph exploration problems in the following natural scenario: an algorithm starts exploring an undirected graph from some seed node; the algorithm, for an arbitrary node $v$ that it is aware of, can ask an oracle to…

Data Structures and Algorithms · Computer Science 2017-10-25 Flavio Chierichetti , Shahrzad Haddadan

We propose an efficient $\epsilon$-differentially private algorithm, that given a simple {\em weighted} $n$-vertex, $m$-edge graph $G$ with a \emph{maximum unweighted} degree $\Delta(G) \leq n-1$, outputs a synthetic graph which…

Data Structures and Algorithms · Computer Science 2023-10-02 Jingcheng Liu , Jalaj Upadhyay , Zongrui Zou

Suppose a graph $G$ is stochastically created by uniformly sampling vertices along a line segment and connecting each pair of vertices with a probability that is a known decreasing function of their distance. We ask if it is possible to…

Data Structures and Algorithms · Computer Science 2020-06-09 Yu Chen , Sampath Kannan , Sanjeev Khanna

In this paper we provide an algorithm that generates a graph with given degree sequence uniformly at random. Provided that $\Delta^4=O(m)$, where $\Delta$ is the maximal degree and $m$ is the number of edges,the algorithm runs in expected…

Combinatorics · Mathematics 2021-01-25 Andrii Arman , Pu Gao , Nicholas Wormald

Graph reconstruction can efficiently detect the underlying topology of massive networks such as the Internet. Given a query oracle and a set of nodes, the goal is to obtain the edge set by performing as few queries as possible. An algorithm…

Data Structures and Algorithms · Computer Science 2024-07-29 Clara Stegehuis , Lotte Weedage

An algorithm observes the trajectories of random walks over an unknown graph $G$, starting from the same vertex $x$, as well as the degrees along the trajectories. For all finite connected graphs, one can estimate the number of edges $m$ up…

Statistics Theory · Mathematics 2018-08-20 Anna Ben-Hamou , Roberto I. Oliveira , Yuval Peres

For given integers $k$ and $\ell$ with $0<\ell< {k \choose 2}$, Alon, Hefetz, Krivelevich and Tyomkyn formulated the following conjecture: When sampling a $k$-vertex subset uniformly at random from a very large graph $G$, then the…

Combinatorics · Mathematics 2020-02-26 Jacob Fox , Lisa Sauermann

We consider the problem of finding all allowed edges in a bipartite graph $G=(V,E)$, i.e., all edges that are included in some maximum matching. We show that given any maximum matching in the graph, it is possible to perform this…

Discrete Mathematics · Computer Science 2011-07-26 Tamir Tassa

In this paper, we give an analytic solution for graphs with n nodes and E edges for which the probability of obtaining a given graph G is specified in terms of the degree sequence of G. We describe how this model naturally appears in the…

Probability · Mathematics 2008-10-20 M. Draief , A. Ganesh , L. Massoulie