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Clustering is a fundamental problem in unsupervised machine learning with many applications in data analysis. Popular clustering algorithms such as Lloyd's algorithm and $k$-means++ can take $\Omega(ndk)$ time when clustering $n$ points in…

Machine Learning · Computer Science 2023-10-26 Moses Charikar , Monika Henzinger , Lunjia Hu , Maxmilian Vötsch , Erik Waingarten

We formulate the statistics of the discrete multicomponent fragmentation event using a methodology borrowed from statistical mechanics. We generate the ensemble of all feasible distributions that can be formed when a single integer…

Statistical Mechanics · Physics 2020-07-03 Themis Matsoukas

A discrete-time stochastic process derived from a model of basketball is used to generalize any discrete distribution. The generalized distributions can have one or two more parameters than the parent distribution. Those derived from…

Applications · Statistics 2020-06-25 Rose Baker

We investigate the problem of growing clusters, which is modeled by two dimensional disks and three dimensional droplets. In this model we place a number of seeds on random locations on a lattice with an initial occupation probability, $p$.…

Statistical Mechanics · Physics 2015-01-28 N. Tsakiris , M. Maragakis , K. Kosmidis , P. Argyrakis

Universal scaling of distances between vertices of Erdos-Renyi random graphs, scale-free Barabasi-Albert models, science collaboration networks, biological networks, Internet Autonomous Systems and public transport networks are observed. A…

Disordered Systems and Neural Networks · Physics 2009-11-10 Janusz A. Holyst , Julian Sienkiewicz , Agata Fronczak , Piotr Fronczak , Krzysztof Suchecki

Consider an unlimited homogeneous medium disturbed by points generated via Poisson process. The neighborhood of a point plays an important role in spatial statistics problems. Here, we obtain analytically the distance statistics to $k$th…

Statistical Mechanics · Physics 2015-08-11 Cristiano Roberto Fabri Granzotti , Alexandre Souto Martinez

We consider the discrete three dimensional scan statistics. Viewed as the maximum of an 1-dependent stationary r.v.'s sequence, we provide approximations and error bounds for the probability distribution of the three dimensional scan…

Computation · Statistics 2013-03-18 Alexandru Amarioarei , Cristian Preda

Let $k,d $ be positive integers. We determine a sequence of constants that are asymptotic to the probability that the cluster at the origin in a $d$-dimensional Poisson Boolean model with balls of fixed radius is of order $k$, as the…

Probability · Mathematics 2025-04-10 Mathew D. Penrose , Xiaochuan Yang

We study the moments and the distribution of the discrete Choquet integral when regarded as a real function of a random sample drawn from a continuous distribution. Since the discrete Choquet integral includes weighted arithmetic means,…

Probability · Mathematics 2015-05-13 Ivan Kojadinovic , Jean-Luc Marichal

We have studied the soliton propagation through a segment containing random point-like scatterers. In the limit of small concentration of scatterers when the mean distance between the scatterers is larger than the soliton width, a method…

In this article, we show that a linear combination $X$ of $n$ independent, unbiased Bernoulli random variables $\{X_k\}$ can match the first $2n$ moments of a random variable $Y$ which is uniform on an interval. More generally, for each $p…

Probability · Mathematics 2019-09-16 Greg Kuperberg

When a disordered array of coupled waveguides is illuminated with an extended coherent optical field, discrete speckle develops: partially coherent light with a granular intensity distribution on the lattice sites. The same paradigm applies…

Optics · Physics 2017-07-11 H. Esat Kondakci , Ayman F. Abouraddy , Bahaa E. A. Saleh

This paper establishes a combinatorial central limit theorem for stratified randomization, which holds under a Lindeberg-type condition. The theorem allows for an arbitrary number or sizes of strata, with the sole requirement being that…

Statistics Theory · Mathematics 2024-04-16 Purevdorj Tuvaandorj

We obtain an explicit formula for the variance of the number of $k$-peaks in a uniformly random permutation. This is then used to obtain an asymptotic formula for the variance of the length of longest $k$-alternating subsequence in random…

Probability · Mathematics 2026-04-15 Recep Altar Çiçeksiz , Yunus Emre Demirci , Ümit Işlak

We consider a translation and dilation invariant system consisting of k diagonal equations of degrees 1,2,...,k with integer coefficients in s variables, where s is sufficiently large in terms of k. We show via the Hardy-Littlewood circle…

Number Theory · Mathematics 2010-10-11 Matthew L. Smith

A central limit theorem is established for a sum of random variables belonging to a sequence of random fields. The fields are assumed to have zero mean conditional on the past history and to satisfy certain conditional $\alpha$-mixing…

Probability · Mathematics 2024-09-17 Abdollah Jalilian , Arnaud Poinas , Ganggang Xu , Rasmus Waagepetersen

We study the compositions of an integer n whose part sizes do not exceed a fixed integer k. We use the methods of analytic combinatorics to obtain precise asymptotic formulas for the number of such compositions, the total number of parts…

Combinatorics · Mathematics 2012-02-08 Martin E. Malandro

We consider density estimators based on the nearest neighbors method applied to discrete point distibutions in spaces of arbitrary dimensionality. If the density is constant, the volume of a hypersphere centered at a random location is…

Instrumentation and Methods for Astrophysics · Physics 2013-01-24 Przemek Wozniak , Andrzej Kruszewski

Discrete sampling theorem is formulated that refers to discrete signals specified by a finite number of their samples and band-limited in a domain of a certain orthogonal transform. Conditions of the recoverability of such signals from…

Optics · Physics 2009-02-24 L. Yaroslavsky

We study numerically propagation of energy in a one dimensional Ding-Ding lattice, composed of linear oscillators with ellastic collisions. Wave propagation is suppressed by breaking translational symmetry, we consider three way to do this:…

Disordered Systems and Neural Networks · Physics 2020-06-24 A. Pikovsky