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A general theory is provided delivering convergence of maximal cyclically monotone mappings containing the supports of coupling measures of sequences of pairs of possibly random probability measures on Euclidean space. The theory is based…

Statistics Theory · Mathematics 2022-08-05 Johan Segers

Consider $n$ points distributed uniformly in $[0,1]^d$. Form a graph by connecting two points if their mutual distance is no greater than $r(n)$. This gives a random geometric graph, $\gnrn$, which is connected for appropriate $r(n)$. We…

Probability · Mathematics 2007-05-23 Sanatan Rai

A sequence of graphs is FO-convergent if the probability of satisfaction of every first-order formula converges. A graph modeling is a graph, whose domain is a standard probability space, with the property that every definable set is Borel.…

Combinatorics · Mathematics 2026-04-15 J. Nesetril , P. Ossona de Mendez

A well-known result of Shelah and Spencer tells us that the almost sure theory for first order language on the random graph sequence $\left\{G(n, cn^{-1})\right\}$ is not complete. This paper proposes and proves what the complete set of…

Probability · Mathematics 2018-02-02 Moumanti Podder

It is well understood that the structure of a social network is critical to whether or not agents can aggregate information correctly. In this paper, we study social networks that support information aggregation when rational agents act…

Theoretical Economics · Economics 2020-11-11 Itai Arieli , Fedor Sandomirskiy , Rann Smorodinsky

This paper studies new properties of the front and back ends of a sorting network, and illustrates the utility of these in the search for new bounds on optimal sorting networks. Search focuses first on the "outsides" of the network and then…

Data Structures and Algorithms · Computer Science 2017-08-09 Michael Codish , Luís Cruz-Filipe , Thorsten Ehlers , Mike Müller , Peter Schneider-Kamp

Given a length $n$ sample from $\mathbb{R}^d$ and a neural network with a fixed architecture with $W$ weights, $k$ neurons, linear threshold activation functions, and binary outputs on each neuron, we study the problem of uniformly sampling…

Machine Learning · Computer Science 2019-12-12 Changlong Wu , Narayana Prasad Santhanam

We investigate the following generalisation of permutation networks. We say a sequence $T=(T_1,\dots,T_\ell)$ of transpositions in $S_n$ forms a $t$-reachability network if, for every choice of $t$ distinct points $x_1, \dots, x_t\in…

Combinatorics · Mathematics 2025-11-05 Carla Groenland , Tom Johnston , Jamie Radcliffe , Alex Scott

Consider the $d$ dimensional lattice $\mathbb{Z}^d$ where each vertex is open or closed with probability $p$ or $1-p$ respectively. An open vertex $\mathbb{u} := (\mathbb{u}(1), \mathbb{u}(2),...,\mathbb{u}(d))$ is connected by an edge to…

Probability · Mathematics 2015-02-27 Rahul Roy , Kumarjit Saha , Anish Sarkar

This article reviews and evaluates models of network evolution based on the notion of structural diversity. We show that diversity is an underlying theme of three principles of network evolution: the preferential attachment model,…

Social and Information Networks · Computer Science 2020-09-22 Jérôme Kunegis

This paper formalizes a latent variable inference problem we call {\em supervised pattern discovery}, the goal of which is to find sets of observations that belong to a single ``pattern.'' We discuss two versions of the problem and prove…

Machine Learning · Statistics 2014-02-10 Jonathan H. Huggins , Cynthia Rudin

Let $S_{n,k}$ denote the random geometric graph obtained by placing points in a square box of area $n$ according to a Poisson process of intensity 1 and joining each point to its $k$ nearest neighbours. Balister, Bollob\'as, Sarkar and…

Probability · Mathematics 2013-02-26 Victor Falgas-Ravry , Mark Walters

Clustering is one of the most common unsupervised learning tasks in machine learning and data mining. Clustering algorithms have been used in a plethora of applications across several scientific fields. However, there has been limited…

Machine Learning · Computer Science 2017-02-09 Quang N. Tran , Ba-Ngu Vo , Dinh Phung , Ba-Tuong Vo

Order the vertices of a directed random graph \math{v_1,...,v_n}; edge \math{(v_i,v_j)} for \math{i<j} exists independently with probability \math{p}. This random graph model is related to certain spreading processes on networks. We…

Combinatorics · Mathematics 2012-09-12 Paul Horn , Malik Magdon-Ismail

The topological information of a network can be retrieved equivalently from its complement consisting of the same nodes but complementary edges. Hence the partition of a network into certain substructures based on given criteria should be…

Physics and Society · Physics 2009-08-07 Jiao Wang , C. -H. Lai

In this paper we introduce a new neural architecture for sorting unordered sequences where the correct sequence order is not easily defined but must rather be inferred from training data. We refer to this architecture as OrderNet and…

Machine Learning · Computer Science 2019-05-29 Robert Porter

Many real life networks, such as the World Wide Web, transportation systems, biological or social networks, achieve both a strong local clustering (nodes have many mutual neighbors) and a small diameter (maximum distance between any two…

Condensed Matter · Physics 2009-11-07 Francesc Comellas , Michael Sampels

A grand challenge in network science is apparently the missing of a structural theory of networks. The authors have showed that the existence of community structures is a universal phenomenon in real networks, and that neither randomness…

Social and Information Networks · Computer Science 2013-11-01 Angsheng Li , Jiankou Li , Yicheng Pan

Consider a graph on randomly scattered points in an arbitrary space, with two points $x,y$ connected with probability $\phi(x,y)$. Suppose the number of points is large but the mean number of isolated points is $O(1)$. We give general…

Probability · Mathematics 2017-09-21 Mathew D. Penrose

In this paper, we consider a queueing network with $N$ nodes, each of which has a fixed number $k$ of neighboring nodes, referred to as the $N$ node network with local balancing. We assume that to each of the $N$ nodes, an incoming job (or…

Probability · Mathematics 2020-01-09 Qihui Bu , Liwei Liu , Yiqiang Q. Zhao