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Drawing on some recent results that provide the formalism necessary to definite stationarity for infinite random graphs, this paper initiates the study of statistical and learning questions pertaining to these objects. Specifically, a…

Machine Learning · Computer Science 2017-08-11 Daniil Ryabko

It is possible to represent each of a number of Markov chains as an evolving sequence of connected subsets of a directed acyclic graph that grow in the following way: initially, all vertices of the graph are unoccupied, particles are fed in…

Probability · Mathematics 2015-03-17 Steven N. Evans , Rudolf Gruebel , Anton Wakolbinger

A new family of tree-structured Markov random fields for a vector of discrete counting random variables is introduced. According to the characteristics of the family, the marginal distributions of the Markov random fields are all Poisson…

Methodology · Statistics 2025-01-20 Benjamin Côté , Hélène Cossette , Etienne Marceau

The success of generative modeling in continuous domains has led to a surge of interest in generating discrete data such as molecules, source code, and graphs. However, construction histories for these discrete objects are typically not…

Machine Learning · Computer Science 2019-11-01 Ari Seff , Wenda Zhou , Farhan Damani , Abigail Doyle , Ryan P. Adams

Markov chains are convenient means of generating realizations of networks with a given (joint or otherwise) degree distribution, since they simply require a procedure for rewiring edges. The major challenge is to find the right number of…

Social and Information Networks · Computer Science 2012-11-01 J. Ray , A. Pinar , C. Seshadhri

We show that an algorithmic construction of sequences of recursive trees leads to a direct proof of the convergence of random recursive trees in an associated Doob-Martin compactification; it also gives a representation of the limit in…

Probability · Mathematics 2014-07-01 Rudolf Grübel , Igor Michailow

We propose a Markov chain simulation method to generate simple connected random graphs with a specified degree sequence and level of clustering. The networks generated by our algorithm are random in all other respects and can thus serve as…

Discrete Mathematics · Computer Science 2010-02-09 Shweta Bansal , Shashank Khandelwal , Lauren Ancel Meyers

A set of independence statements may define the independence structure of interest in a family of joint probability distributions. This structure is often captured by a graph that consists of nodes representing the random variables and of…

Methodology · Statistics 2011-07-15 Nanny Wermuth

In this paper we investigate phenomena of spontaneous emergence or purposeful formation of highly organized structures in networks of related agents. We show that the formation of large organized structures requires exponentially large, in…

Cryptography and Security · Computer Science 2023-04-11 V. Liagkou , P. E. Nastou , P. Spirakis , Y. C. Stamatiou

The extremal characteristics of random structures, including trees, graphs, and networks, are discussed. A statistical physics approach is employed in which extremal properties are obtained through suitably defined rate equations. A variety…

Statistical Mechanics · Physics 2007-05-23 E. Ben-Naim , P. L. Krapivsky , S. Redner

In many branches of engineering, Banach contraction mapping theorem is employed to establish the convergence of certain deterministic algorithms. Randomized versions of these algorithms have been developed that have proved useful in…

Probability · Mathematics 2023-09-25 Abhishek Gupta , Rahul Jain , Peter Glynn

We study the joint occurrence of large values of a Markov random field or undirected graphical model associated to a block graph. On such graphs, containing trees as special cases, we aim to generalize recent results for extremes of Markov…

Methodology · Statistics 2023-03-09 Stefka Asenova , Johan Segers

In this paper we investigate the use of staged tree models for discrete longitudinal data. Staged trees are a type of probabilistic graphical model for finite sample space processes. They are a natural fit for longitudinal data because a…

Methodology · Statistics 2024-01-10 Jack Storror Carter , Manuele Leonelli , Eva Riccomagno , Alessandro Ugolini

We report a rigorous theory to show the origin of the unexpected periodic behavior seen in the consecutive differences between prime numbers. We also check numerically our findings to ensure that they hold for finite sequences of primes,…

Statistical Mechanics · Physics 2007-05-23 Saul Ares , Mario Castro

I start by reviewing some basic properties of random graphs. I then consider the role of random walks in complex networks and show how they may be used to explain why so many long tailed distributions are found in real data sets. The key…

Statistical Mechanics · Physics 2012-12-11 T. S. Evans

We investigate the behavior of data structures when the input and operations are generated by an event graph. This model is inspired by Markov chains. We are given a fixed graph G, whose nodes are annotated with operations of the type…

Data Structures and Algorithms · Computer Science 2015-03-10 Bernard Chazelle , Wolfgang Mulzer

The paper formulates the concept of persistence of excitation for discrete-time linear switched systems, and provides sufficient conditions for an input signal to be persistently exciting. Persistence of excitation is formulated as a…

Optimization and Control · Mathematics 2011-03-08 Mihaly Petreczky , Laurent Bako

Infinite random sequences of letters can be viewed as stochastic chains or as strings produced by a source, in the sense of information theory. The relationship between Variable Length Markov Chains (VLMC) and probabilistic dynamical…

Probability · Mathematics 2010-07-20 Peggy Cénac , Brigitte Chauvin , Frédéric Paccaut , Nicolas Pouyanne

Hypergraphs are structures that can be decomposed or described; in other words they are recursively countable. Here, we get exact and asymptotic enumeration results on hypergraphs by means of exponential generating functions. The number of…

Discrete Mathematics · Computer Science 2008-06-20 Tsiriniaina Andriamampianina

We consider random filtered complexes built over marked point processes on Euclidean spaces. Examples of our filtered complexes include a filtration of $\check{\textrm{C}}$ech complexes of a family of sets with various sizes, growths, and…

Probability · Mathematics 2021-03-17 Tomoyuki Shirai , Kiyotaka Suzaki
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