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We present an algorithm that efficiently computes nearly-optimal solutions to a class of combinatorial reconfiguration problems on weighted, undirected graphs. Inspired by societally relevant applications in networked infrastructure…

Optimization and Control · Mathematics 2025-10-29 Samuel Talkington , Dmitrii M. Ostrovskii , Daniel K. Molzahn

We consider two classes of natural stochastic processes on finite unlabeled graphs. These are Euclidean stochastic optimization algorithms on the adjacency matrix of weighted graphs and a modified version of the Metropolis MCMC algorithm on…

Probability · Mathematics 2023-10-17 Siva Athreya , Soumik Pal , Raghav Somani , Raghavendra Tripathi

The logistic regression model is known to converge to a Poisson point process model if the binary response tends to infinitely imbalanced. In this paper, it is shown that this phenomenon is universal in a wide class of link functions on…

Statistics Theory · Mathematics 2013-04-23 Tomonari Sei

We consider a random partition of the vertex set of an arbitrary graph that can be sampled using loop-erased random walks stopped at a random independent exponential time of parameter $q>0$, that we see as a tuning parameter.The related…

Probability · Mathematics 2020-07-15 Luca Avena , Alexandre Gaudilliere , Paolo Milanesi , Matteo Quattropani

We prove that the local limit of the weighted spanning trees on any simple connected high degree almost regular sequence of electric networks is the Poisson(1) branching process conditioned to survive forever, by generalizing [NP22] and…

Probability · Mathematics 2026-01-01 Ágnes Kúsz

The semiclassical limit of full non-commutative gauge theory is known as Poisson gauge theory. In this work we revise the construction of Poisson gauge theory paying attention to the geometric meaning of the structures involved and advance…

High Energy Physics - Theory · Physics 2022-11-30 V. G. Kupriyanov , M. A. Kurkov , P. Vitale

We consider the model of random interlacements on transient graphs, which was first introduced by Sznitman [Ann. of Math. (2) (2010) 171 2039-2087] for the special case of ${\mathbb{Z}}^d$ (with $d\geq3$). In Sznitman [Ann. of Math. (2)…

Probability · Mathematics 2013-03-15 Augusto Teixeira , Johan Tykesson

Non-homogeneous Poisson processes are used in a wide range of scientific disciplines, ranging from the environmental sciences to the health sciences. Often, the central object of interest in a point process is the underlying intensity…

Methodology · Statistics 2022-02-11 Tin Lok James Ng , Andrew Zammit-Mangion

This work presents a non-parametric estimator for the cumulative distribution function (CDF) of the job-size distribution for a queue with compound Poisson input. The workload process is observed according to an independent Poisson sampling…

Statistics Theory · Mathematics 2025-12-11 Liron Ravner

Exchangeability is a central notion in statistics and probability theory. The assumption that an infinite sequence of data points is exchangeable is at the core of Bayesian statistics. However, finite exchangeability as a statistical…

Artificial Intelligence · Computer Science 2014-04-24 Mathias Niepert , Guy Van den Broeck

We consider random transformations $T_\omega^n:=T_{\sigma^{n-1}\omega}\circ\cdots\circ T_{\sigma\omega}\circ T_\omega,$ where each map $T_{\omega}$ acts on a complete metrizable space $M$. The randomness comes from an invertible ergodic…

Dynamical Systems · Mathematics 2024-02-21 Jason Atnip , Gary Froyland , Cecilia González-Tokman , Sandro Vaienti

Disordered complex networks are of fundamental interest as stochastic models for information transmission over wireless networks. Well-known networks based on the Poisson point process model have limitations vis-a-vis network efficiency,…

Signal Processing · Electrical Eng. & Systems 2022-03-14 Subhro Ghosh , Naoto Miyoshi , Tomoyuki Shirai

We show the convergence of the characteristic polynomial for random permutation matrices sampled from the generalized Ewens distribution. Under this distribution, the measure of a given permutation depends only on its cycle structure,…

Combinatorics · Mathematics 2025-12-05 Quentin François

We give a deterministic algorithm to construct a graph with no loops (a tree or a forest) whose vertices are the points of a d-dimensional stationary Poisson process S, subset of R^d. The algorithm is independent of the origin of…

Probability · Mathematics 2011-11-10 P. A. Ferrari , C. Landim , H. Thorisson

We prove a general theorem on cutoffs for symmetric exclusion and interchange processes on finite graphs $G_N=(V_N,E_N)$, under the assumption that either the graphs converge geometrically and spectrally to a compact metric measure space,…

Probability · Mathematics 2020-12-24 Joe P. Chen , Rodrigo Marinho

Consider a stationary Poisson process $\eta$ in the $d$-dimensional Euclidean or hyperbolic space and construct a random graph with vertex set $\eta$ as follows. First, each point $x\in\eta$ is connected by an edge to its nearest neighbour,…

Probability · Mathematics 2024-11-04 Holger Sambale , Christoph Thäle , Tara Trauthwein

We present a procedure to sample uniformly from the set of combinatorial isomorphism types of balanced triangulations of surfaces - also known as graph-encoded surfaces. For a given number $n$, the sample is a weighted set of graph-encoded…

Combinatorics · Mathematics 2022-11-16 Rajan Shankar , Jonathan Spreer

In 1986, Janson showed that the number of edges in the union of $k$ random spanning trees in the complete graph $K_n$ is a shifted Poisson distribution. Using results from the theory of electrical networks, we provide a new proof of this…

Combinatorics · Mathematics 2020-02-17 Austen James , Matthew Larson , Daniel Montealegre , Andrew Salmon

In a number of recent papers, the idea of generalized boundaries has found use in fractal and in multiresolution analysis; many of the papers having a focus on specific examples. Parallel with this new insight, and motivated by quantum…

Functional Analysis · Mathematics 2018-05-17 Palle Jorgensen , Feng Tian

We develop correlated random measures, random measures where the atom weights can exhibit a flexible pattern of dependence, and use them to develop powerful hierarchical Bayesian nonparametric models. Hierarchical Bayesian nonparametric…

Machine Learning · Statistics 2016-11-10 Rajesh Ranganath , David Blei
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