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Stochastic linear combinations of some random vectors are studied where the distribution of the random vectors and the joint distribution of their coefficients are Dirichlet. A method is provided for calculating the distribution of these…

Statistics Theory · Mathematics 2016-03-03 Hazhir Homei

Let $G$ be a connected edge-weighted graph of order $n$ and size $m$. Let $w:E(G)\rightarrow \mathbb{R}^{\geq 0}$ be the weighting function. We assume that $w$ is normalised, that is, $\sum_{e\in E(G)} w(e)=m$. The weighted distance…

Combinatorics · Mathematics 2020-10-13 Peter Johnson , Fadekemi Janet Osaye

We present a new notion of limits of weighted directed graphs of growing size based on convergence of their random quotients. These limits are specified in terms of random exchangeable measures on the unit square. We call our limits…

Combinatorics · Mathematics 2026-03-24 Eitan Levin , Venkat Chandrasekaran

Let $H=(V,E)$ be an $r$-uniform hypergraph with the vertex set $V$ and the edge set $E$. For $1\leq s \leq r/2$, we define a weighted graph $G^{(s)}$ on the vertex set ${V\choose s}$ as follows. Every pair of $s$-sets $I$ and $J$ is…

Combinatorics · Mathematics 2011-12-06 Linyuan Lu , Xing Peng

One problem of wide interest involves estimating expected crossing-times. Several tools have been developed to solve this problem beginning with the works of Wald and the theory of sequential analysis. An extension of his approach is…

Methodology · Statistics 2015-06-17 Mark Brown , Victor de la Pena , Tony Sit

We prove a formula for the asymptotic number of edge-colored regular graphs with a prescribed set of allowed vertex-incidence structures. The formula depends on specific critical points of a polynomial encoding the vertex-incidences. As an…

Combinatorics · Mathematics 2026-01-28 Michael Borinsky , Chiara Meroni , Maximilian Wiesmann

We study the limit theory of large threshold graphs and apply this to a variety of models for random threshold graphs. The results give a nice set of examples for the emerging theory of graph limits.

Combinatorics · Mathematics 2009-08-19 Persi Diaconis , Susan Holmes , Svante Janson

Assume that the edges of the complete graph $K_n$ are given independent uniform $[0,1]$ edges weights. We consider the expected minimum total weight $\mu_k$ of $k\geq 2$ edge disjoint spanning trees. When $k$ is large we show that…

Combinatorics · Mathematics 2017-06-23 Alan Frieze , Tony Johansson

We study the minimum spanning tree problem on the complete graph $K_n$ where an edge $e$ has a weight $W_e$ and a cost $C_e$, each of which is an independent copy of the random variable $U^\gamma$ where $\gamma\leq 1$ and $U$ is the uniform…

Combinatorics · Mathematics 2021-06-01 Alan Frieze , Tomasz Tkocz

Let the class A of graphs be bridge-addable; that is, whenever a graph G in A has vertices u and v in different components then the graph G+uv is in A. For a random graph sampled uniformly from the graphs in A on vertex set {1,..,n}, there…

Combinatorics · Mathematics 2020-06-04 Colin McDiarmid

For a given permutation $\pi_n$ in $S_n$, a random permutation graph is formed by including an edge between two vertices $i$ and $j$ if and only if $(i - j) (\pi_n(i) - \pi_n (j)) < 0$. In this paper, we study various statistics of random…

Combinatorics · Mathematics 2021-08-02 Oğuz Gürerk , Ümit Işlak , Mehmet Akif Yıldız

We study the asymptotic properties of distributed consensus algorithms over switching directed random networks. More specifically, we focus on consensus algorithms over independent and identically distributed, directed random graphs, where…

Multiagent Systems · Computer Science 2010-04-21 Victor M. Preciado , Alireza Tahbaz-Salehi , Ali Jadbabaie

A random graph evolution rule is considered. The graph evolution is based on interactions of three vertices. The weight of a clique is the number of its interactions. The asymptotic behaviour of the weights is described. It is known that…

Probability · Mathematics 2014-12-23 István Fazekas , Csaba Noszály , Attila Perecsényi

We investigate the expected value of various graph parameters associated with the minimum rank of a graph, including minimum rank/maximum nullity and related Colin de Verdi\`ere-type parameters. Let $G(v,p)$ denote the usual…

Combinatorics · Mathematics 2016-05-24 Tracy Hall , Leslie Hogben , Ryan R. Martin , Bryan Shader

Structured prediction tasks in machine learning involve the simultaneous prediction of multiple labels. This is typically done by maximizing a score function on the space of labels, which decomposes as a sum of pairwise elements, each…

Machine Learning · Computer Science 2014-09-23 Amir Globerson , Tim Roughgarden , David Sontag , Cafer Yildirim

Traffic fluctuation has so far been studied on unweighted networks. However many real traffic systems are better represented as weighted networks, where nodes and links are assigned a weight value representing their physical properties such…

Statistical Mechanics · Physics 2011-11-11 Yichao Zhang , Shi Zhou , Zhongzhi Zhang , Jihong Guan , Shuigeng Zhou , Guanrong Chen

We consider a linearly edge-reinforced random walk on a class of two-dimensional graphs with constant initial weights. The graphs are obtained from $\mathbb{Z}^2$ by replacing every edge by a sufficiently large, but fixed number of edges in…

Probability · Mathematics 2009-10-13 Franz Merkl , Silke W. W. Rolles

We consider the down/up crossing property of weighted Markov branching processes. The joint probability distribution of multi crossing numbers of such processes are obtained. In particular, for Markov branching processes, the probability…

Probability · Mathematics 2020-04-20 Yanyun Li , Junping Li

In the stochastic weighted matching problem, the goal is to find a large-weight matching of a graph when we are uncertain about the existence of its edges. In particular, each edge $e$ has a known weight $w_e$ but is realized independently…

Data Structures and Algorithms · Computer Science 2022-11-01 Mahsa Derakhshan , Alireza Farhadi

Network (graph) data analysis is a popular research topic in statistics and machine learning. In application, one is frequently confronted with graph two-sample hypothesis testing where the goal is to test the difference between two graph…

Methodology · Statistics 2021-02-01 Mingao Yuan , Qian Wen
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