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We consider a connected undirected graph $G(n,m)$ with $n$ nodes and $m$ edges. A $k$-dominating set $D$ in $G$ is a set of nodes having the property that every node in $G$ is at most $k$ edges away from at least one node in $D$. Finding a…

Distributed, Parallel, and Cluster Computing · Computer Science 2007-05-23 L. D. Penso , V. C. Barbosa

We propose two efficient algorithms for generating uniform random directed acyclic graphs, including an asymptotically optimal exact-size sampler that performs $\frac{n^2}{2} + o(n^2)$ operations and requests to a random generator. This was…

Data Structures and Algorithms · Computer Science 2026-02-10 Wojciech Gabryelski , Zbigniew Gołȩbiewski , Martin Pépin

In statistical mechanical investigations on complex networks, it is useful to employ random graphs ensembles as null models, to compare with experimental realizations. Motivated by transcription networks, we present here a simple way to…

Statistical Mechanics · Physics 2009-11-11 F. Bassetti , M. Cosentino Lagomarsino , B. Bassetti , P. Jona

We introduce a Markov Chain Monte Carlo algorithm which samples from the space of spanning trees of complete graphs using local rewiring operations only. The probability distribution of graphs of this kind is shown to depend on the…

Discrete Mathematics · Computer Science 2017-11-21 Neal McBride , John Bulava

In previous papers, threshold probabilities for the properties of a random distance graph to contain strictly balanced graphs were found. We extend this result to arbitrary graphs and prove that the number of copies of a strictly balanced…

Combinatorics · Mathematics 2018-05-09 A. V. Burkin , M. E. Zhukovskii

We study semiorders induced by points drawn from a uniform random distribution. Of particular interest in this paper are the probabilities of generating specific semiorders and the equivalence classes they produce. We present a method for…

Combinatorics · Mathematics 2025-09-25 Csaba Biró , Caroline E. Boone

A variety of network modeling problems begin by generating a degree sequence drawn from a given probability distribution. If the randomly generated sequence is not graphic, we give a new approach for generating a graphic approximation of…

Discrete Mathematics · Computer Science 2017-12-19 Brian Cloteaux

We prove the unexpected result that almost uniform sampling of independent sets in graphs is possible via a probabilistic polynomial time algorithm. Note that our sampling algorithm (if correct) has extremely surprising consequences; the…

Computational Complexity · Computer Science 2023-12-20 Andras Farago

An important problem arising in the study of complex networks, for instance in community detection and motif finding, is the sampling of graphs with fixed degree sequence. The equivalent problem of generating random 0,1 matrices with fixed…

Combinatorics · Mathematics 2018-07-27 Annabell Berger , Corrie Jacobien Carstens

One of the most influential recent results in network analysis is that many natural networks exhibit a power-law or log-normal degree distribution. This has inspired numerous generative models that match this property. However, more recent…

Data Structures and Algorithms · Computer Science 2011-09-01 Isabelle Stanton , Ali Pinar

In this work we present a simple and efficient algorithm which, with high probability, provides an almost uniform sample from the set of proper k-colourings on an instance of a sparse random graph G(n,d/n), where k=k(d) is a sufficiently…

Discrete Mathematics · Computer Science 2008-06-26 Charilaos Efthymiou , Paul G. Spirakis

Unbiased random vectors i.e. distributed uniformly in n-dimensional space, are widely applied and the computational cost of generating a vector increases only linearly with n. On the other hand, generating uniformly distributed random…

Numerical Analysis · Mathematics 2021-04-05 Arun I. , Murugesan Venkatapathi

We present a comprehensive extension of the latent position network model known as the random dot product graph to accommodate multiple graphs -- both undirected and directed -- which share a common subset of nodes, and propose a method for…

Machine Learning · Statistics 2021-01-26 Andrew Jones , Patrick Rubin-Delanchy

We propose a fast approximate algorithm for large graph matching. A new projected fixed-point method is defined and a new doubly stochastic projection is adopted to derive the algorithm. Previous graph matching algorithms suffer from high…

Computer Vision and Pattern Recognition · Computer Science 2012-08-13 Yao Lu , Kaizhu Huang , Cheng-Lin Liu

Given two distributions F and G on the nonnegative integers we propose an algorithm to construct in- and out-degree sequences from samples of i.i.d. observations from F and G, respectively, that with high probability will be graphical, that…

Probability · Mathematics 2012-07-12 Ningyuan Chen , Mariana Olvera-Cravioto

Distributionally balanced sampling designs are low-discrepancy probability designs obtained by minimizing the expected discrepancy between the auxiliary-variable distribution of a random sample and the target population distribution.…

Methodology · Statistics 2026-03-26 Anton Grafström , Wilmer Prentius

A sorting network is a shortest path from 12..n to n..21 in the Cayley graph of the symmetric group S(n) generated by nearest-neighbor swaps. A pattern is a sequence of swaps that forms an initial segment of some sorting network. We prove…

Probability · Mathematics 2012-11-21 Omer Angel , Vadim Gorin , Alexander E. Holroyd

We consider a generalized poset sorting problem (GPS), in which we are given a query graph $G = (V, E)$ and an unknown poset $\mathcal{P}(V, \prec)$ that is defined on the same vertex set $V$, and the goal is to make as few queries as…

Data Structures and Algorithms · Computer Science 2023-07-18 Shaofeng H. -C. Jiang , Wenqian Wang , Yubo Zhang , Yuhao Zhang

The generation of random graphs using edge swaps provides a reliable method to draw uniformly random samples of sets of graphs respecting some simple constraints, e.g. degree distributions. However, in general, it is not necessarily…

Social and Information Networks · Computer Science 2012-02-06 Lionel Tabourier , Camille Roth , Jean-Philippe Cointet

We show how to generate random derangements efficiently by two different techniques: random restricted transpositions and sequential importance sampling. The algorithm employing restricted transpositions can also be used to generate random…

Computation · Statistics 2020-08-17 J. R. G. Mendonça