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Sum-of-norms clustering is a convex optimization problem whose solution can be used for the clustering of multivariate data. We propose and study a localized version of this method, and show in particular that it can separate arbitrarily…

Machine Learning · Computer Science 2024-07-16 Alexander Dunlap , Jean-Christophe Mourrat

Clusters appear in nature in a diversity of contexts, involving distances as long as the cosmological ones, and down to atoms and molecules and the very small nuclear size. They also appear in several other scenarios, in particular in…

Populations and Evolution · Quantitative Biology 2020-02-19 D. Bazeia , M. V. de Moraes , B. F. de Oliveira

The following random recurrency: $$ W_{n+1} = U_{n+1} ( W_n + \Lambda_{n+1} ) $$ where $W_{-1}=0.$ is known to be associated with the shot noise : $$ W_{t} = \sum_{0<t_k<t} \Lambda_{k} e^{-(t-t_k)} $$ where the $t_k$ are the dates of a…

Probability · Mathematics 2013-12-05 Jean-François Chamayou

We consider stationary configurations of points in Euclidean space which are marked by positive random variables called scores. The scores are allowed to depend on the relative positions of other points and outside sources of randomness.…

Probability · Mathematics 2025-06-25 Bojan Basrak , Ilya Molchanov , Hrvoje Planinić

We begin by reviewing some probabilistic results about the Dirichlet Process and its close relatives, focussing on their implications for statistical modelling and analysis. We then introduce a class of simple mixture models in which…

Methodology · Statistics 2010-03-23 Peter J. Green

We present a Bayesian inference approach to estimating the cumulative mass profile and mean squared velocity profile of a globular cluster given the spatial and kinematic information of its stars. Mock globular clusters with a range of…

Astrophysics of Galaxies · Physics 2022-03-09 Gwendolyn M. Eadie , Jeremy J. Webb , Jeffrey S. Rosenthal

Many models for point process data are defined through a thinning procedure where locations of a base process (often Poisson) are either kept (observed) or discarded (thinned). In this paper, we go back to the fundamentals of the…

Methodology · Statistics 2024-12-12 Renaud Alie , David A. Stephens , Alexandra M. Schmidt

Ample experimental evidence has been accumulated demonstrating that the formation of monodispersed colloids proceeds through a more complex mechanism, than the generally excepted diffusional "burst nucleation" process. Instead, the…

Materials Science · Physics 2010-09-22 Jongsoon Park , Vladimir Privman , Egon Matijevic

Diffusion models generate high-quality synthetic data. They operate by defining a continuous-time forward process which gradually adds Gaussian noise to data until fully corrupted. The corresponding reverse process progressively "denoises"…

Aims. We investigate the contribution of shot-noise and sample variance to the uncertainty of cosmological parameter constraints inferred from cluster number counts in the context of the Euclid survey. Methods. By analysing 1000 Euclid-like…

A detailed simple model is applied to study a metallic cluster. It is assumed that the ions and delocalized electrons are distributed randomly throughout the cluster. The delocalized electrons are assumed to be degenerate. A spherical ball…

Materials Science · Physics 2011-03-01 Yuri Kornyushin

We present a stochastic version of the mean-shift clustering algorithm. In this stochastic version a randomly chosen sequence of data points move according to partial gradient ascent steps of the objective function. Theoretical results…

Machine Learning · Computer Science 2025-11-13 Itshak Lapidot , Yann Sepulcre , Tom Trigano

A computational theory for clustering and a semi-supervised clustering algorithm is presented. Clustering is defined to be the obtainment of groupings of data such that each group contains no anomalies with respect to a chosen grouping…

Machine Learning · Computer Science 2025-07-17 Nassir Mohammad

We use experiments to study the evolution of bubble clusters in a swarm of freely rising, deformable bubbles. A new machine learning-aided algorithm allows us to identify and track bubbles in clusters and measure the cluster lifetimes. The…

Fluid Dynamics · Physics 2023-06-08 Tian Ma , Hendrik Hessenkemper , Dirk Luca , Andrew D. Bragg

We present results from a study of the X-ray cluster population that forms within the CLEF cosmological hydrodynamics simulation, a large N-body/SPH simulation of the Lambda CDM cosmology with radiative cooling, star formation and feedback.…

Consider sequential packing of unit balls in a large cube, as in the Renyi car-parking model, but in any dimension and with Poisson input. We show after suitable rescaling that the spatial distribution of packed balls tends to that of a…

Probability · Mathematics 2007-05-23 Yu. Baryshnikov , J. E. Yukich

This paper is focused on a class of spatial birth and death process of the Euclidean space where the birth rate is constant and the death rate of a given point is the shot noise created at its location by the other points of the current…

Probability · Mathematics 2014-09-01 Francois Baccelli , Fabien Mathieu , Ilkka Norros

A continuously measured quantum system with multiple jump channels gives rise to a stochastic process described by random jump times and random emitted symbols, representing each jump channel. While much is known about the waiting time…

Quantum Physics · Physics 2023-06-21 Gabriel T. Landi

A microscopic model of adsorption in cluster forming systems with competing interaction is considered. The adsorption process is described by the master equation and modelled by a kinetic Monte Carlo method. The evolution of the particle…

Soft Condensed Matter · Physics 2021-09-07 E. Bildanau , V. Vikhrenko

We consider the problem of clustering in the presence of noise. That is, when on top of cluster structure, the data also contains a subset of \emph{unstructured} points. Our goal is to detect the clusters despite the presence of many…

Machine Learning · Computer Science 2018-08-28 Shrinu Kushagra , Yaoliang Yu , Shai Ben-David