English
Related papers

Related papers: Type Size Code for Compressing Erd\"os-R\'enyi Gra…

200 papers

A technique of lossless compression via substring enumeration (CSE) attains compression ratios as well as popular lossless compressors for one-dimensional (1D) sources. The CSE utilizes a probabilistic model built from the circular string…

Information Theory · Computer Science 2017-01-25 Takahiro Ota , Hiroyoshi Morita

We propose a fast methodology for encoding graphs with information-theoretically minimum numbers of bits. Specifically, a graph with property pi is called a pi-graph. If pi satisfies certain properties, then an n-node m-edge pi-graph G can…

Data Structures and Algorithms · Computer Science 2007-05-23 Xin He , Ming-Yang Kao , Hsueh-I Lu

In the classical Erd\"os-R\'enyi random graph G(n,p) there are n vertices and each of the possible edges is independently present with probability p. The random graph G(n,p) is homogeneous in the sense that all vertices have the same…

Combinatorics · Mathematics 2016-02-10 Mihyun Kang , Angelica Pachón , Pablo M. Rodriguez

We consider 15 properties of labeled random graphs that are of interest in the graph-theoretical and the graph mining literature, such as clustering coefficients, centrality measures, spectral radius, degree assortativity, treedepth,…

Social and Information Networks · Computer Science 2022-06-24 Hang Chen , Vahan Huroyan , Stephen Kobourov , Myroslav Kryven

This work focuses on the problem of learning an unknown $3$-uniform hypergraph using edge-detecting queries. Our goal is to design a querying strategy that recovers the hyperedge set using as few queries as possible. We restrict our…

Information Theory · Computer Science 2026-05-12 Huy Pham , Hoang Ta

We introduce a natural generalization of the Erd\H{o}s-R\'enyi random graph model in which random instances of a fixed motif are added independently. The binomial random motif graph $G(H,n,p)$ is the random (multi)graph obtained by adding…

Combinatorics · Mathematics 2019-07-30 Michael Anastos , Peleg Michaeli , Samantha Petti

Upper exponential inequalities for the tail probabilities of the centered and normalized number of triangles in the Erd\"{o}s-R\'{e}nyi graph are obtained, where the probability of every edge is fixed. The result is formulated in terms of…

Probability · Mathematics 2022-03-21 Alexander Bystrov , Nadezhda Volodko

We consider general Exponential Random Graph Models (ERGMs) where the sufficient statistics are functions of homomorphism counts for a fixed collection of simple graphs $F_k$. Whereas previous work has shown a degeneracy phenomenon in dense…

Probability · Mathematics 2024-04-04 Nicholas A. Cook , Amir Dembo

We analyze conformational properties of branched polymer structures, formed on the base of Erd\"os-R\'enyi random graph model. We consider networks with $N=5$ vertices and variable parameter $c$, that controls graph connectedness. The…

Disordered Systems and Neural Networks · Physics 2020-06-24 V. Blavatska , K. Haydukivska , Yu. Holovatch

In this paper, we present a novel way to summarize the structure of large graphs, based on non-parametric estimation of edge density in directed multigraphs. Following coclustering approach, we use a clustering of the vertices, with a…

Social and Information Networks · Computer Science 2015-08-07 Marc Boullé

We derive a simple formula characterizing the distribution of the size of the connected component of a fixed vertex in the Erd\H{o}s-R\'enyi random graph which allows us to give elementary proofs of some results of Federico, van der…

Probability · Mathematics 2018-04-27 Balazs Rath

Exponential random graph models (ERGMs) are flexible probability models allowing edge dependency. However, it is known that, to a first-order approximation, many ERGMs behave like Erd\"os-R\'enyi random graphs, where edges are independent.…

Probability · Mathematics 2024-01-04 Wen-Yi Ding , Xiao Fang

The problem of aligning Erd\"os-R\'enyi random graphs is a noisy, average-case version of the graph isomorphism problem, in which a pair of correlated random graphs is observed through a random permutation of their vertices. We study a…

Information Theory · Computer Science 2022-06-10 Giovanni Piccioli , Guilhem Semerjian , Gabriele Sicuro , Lenka Zdeborová

The problem of detecting edge correlation between two Erd\H{o}s-R\'enyi random graphs on $n$ unlabeled nodes can be formulated as a hypothesis testing problem: under the null hypothesis, the two graphs are sampled independently; under the…

Probability · Mathematics 2022-05-31 Jian Ding , Hang Du

We study a model of random weighted uniform spanning trees on the complete graph with $n$ vertices, where each edge is assigned a weight of $n^{1+\gamma}$ with probability $1/n$ and $1$ otherwise. Whenever $\gamma$ is large enough, we prove…

Probability · Mathematics 2025-12-29 Umberto De Ambroggio , Luca Makowiec

Networks provide a popular representation of complex data. Often, different types of relational measurements are taken on the same subjects. Such data can be represented as a \textit{multislice network}, a collection of networks on the same…

Probability · Mathematics 2025-04-02 Kevin Ren , Tara Trauthwein , Gesine Reinert

We propose and investigate a unifying class of sparse random graph models, based on a hidden coloring of edge-vertex incidences, extending an existing approach, Random graphs with a given degree distribution, in a way that admits a…

Statistical Mechanics · Physics 2009-11-10 Bo Söderberg

We consider two independent Erd\H{o}s-R\'enyi random graphs, with possibly different parameters, and study two isomorphism problems, a graph embedding problem and a common subgraph problem. Under certain conditions on the graph parameters…

Combinatorics · Mathematics 2025-06-25 Dimitris Diamantidis , Takis Konstantopoulos , Linglong Yuan

We present shuffle coding, a general method for optimal compression of sequences of unordered objects using bits-back coding. Data structures that can be compressed using shuffle coding include multisets, graphs, hypergraphs, and others. We…

Machine Learning · Computer Science 2024-08-19 Julius Kunze , Daniel Severo , Giulio Zani , Jan-Willem van de Meent , James Townsend

Rank 1 inhomogeneous random graphs are a natural generalization of Erd\H{o}s R\'enyi random graphs. In this generalization each node is given a weight. Then the probability that an edge is present depends on the product of the weights of…

Probability · Mathematics 2021-07-28 Othmane Safsafi