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In this paper we introduce a new clustering technique called Regularity Clustering. This new technique is based on the practical variants of the two constructive versions of the Regularity Lemma, a very useful tool in graph theory. The…

Combinatorics · Mathematics 2012-10-01 Gábor N. Sárközy , Fei Song , Endre Szemerédi , Shubhendu Trivedi

It is shown that preferential concentrations of inertial (finite-size) particle suspensions in turbulent flows follow from the dissipative nature of their dynamics. In phase space, particle trajectories converge toward a dynamical fractal…

Chaotic Dynamics · Physics 2009-11-10 Jeremie Bec

We study the nucleation of crystalline cluster phases in the generalized exponential model with exponent n=4. Due to the finite value of this pair potential for zero separation, at high densities the system forms cluster crystals with…

Soft Condensed Matter · Physics 2016-09-01 Christian Leitold , Christoph Dellago

In this article, we consider a sequence $(N_n)_{n \geq 1}$ of point processes, whose points lie in a subset $E$ of $\bR \verb2\2 \{0\}$, and satisfy an asymptotic independence condition. Our main result gives some necessary and sufficient…

Probability · Mathematics 2010-11-17 Raluca Balan , Sana Louhichi

Given a set of variables and the correlations among them, we develop a method for finding clustering among the variables. The method takes advantage of information implicit in higher-order (not just pairwise) correlations. The idea is to…

Statistical Mechanics · Physics 2015-05-13 L. S. Schulman

We study the problem of explainability-first clustering where explainability becomes a first-class citizen for clustering. Previous clustering approaches use decision trees for explanation, but only after the clustering is completed. In…

Machine Learning · Computer Science 2022-12-13 Hyunseung Hwang , Steven Euijong Whang

We present a technique for clustering categorical data by generating many dissimilarity matrices and averaging over them. We begin by demonstrating our technique on low dimensional categorical data and comparing it to several other…

Machine Learning · Statistics 2017-09-20 Saeid Amiri , Bertrand Clarke , Jennifer Clarke

We establish a general framework for developing approximation algorithms for a class of counting problems. Our framework is based on the cluster expansion of abstract polymer models formalism of Koteck\'y and Preiss. We apply our framework…

Quantum Physics · Physics 2024-01-18 Ryan L. Mann , Romy M. Minko

We present the clustering of galaxy clusters as a useful addition to the common set of cosmological observables. The clustering of clusters probes the large-scale structure of the Universe, extending galaxy clustering analysis to the…

Cosmology and Nongalactic Astrophysics · Physics 2014-02-03 Annalisa Mana , Tommaso Giannantonio , Jochen Weller , Ben Hoyle , Gert Huetsi , Barbara Sartoris

Despite the widespread use of Clustering, there is distressingly little general theory of clustering available. Questions like "What distinguishes a clustering of data from other data partitioning?", "Are there any principles governing all…

Machine Learning · Computer Science 2012-05-14 Reza Bosagh Zadeh , Shai Ben-David

We calculate the Lyapunov exponents for particles suspended in a random three-dimensional flow, concentrating on the limit where the viscous damping rate is small compared to the inverse correlation time. In this limit Lyapunov exponents…

Disordered Systems and Neural Networks · Physics 2009-11-11 K. Duncan , B. Mehlig , S. Ostlund , M. Wilkinson

We study internal diffusion limited aggregation on $\mathbb{Z}$, where a cluster is grown incrementally by adding, for each random walk dispatched from the origin, the first site it reaches outside the cluster. We assume that the increment…

Probability · Mathematics 2026-03-11 Conrado da Costa , Debleena Thacker , Andrew Wade

In this paper a relative number density parameter, called the neighborhood function, is introduced so that the crowded nature of the neighborhood of individual sources can be described. With this parameter one can determine the probability…

Astrophysics · Physics 2009-11-13 Yi-Ping Qin , Lian-Zhong Lv , Fu-Wen Zhang , Bin-Bin Zhang , Jin Zhang

Identification of the clusters from an unlabeled data set is one of the most important problems in Unsupervised Machine Learning. The state of the art clustering algorithms are based on either the statistical properties or the geometric…

Machine Learning · Computer Science 2018-01-04 Sambarta Dasgupta , Keivan Ebrahimi , Umesh Vaidya

A main task in data analysis is to organize data points into coherent groups or clusters. The stochastic block model is a probabilistic model for the cluster structure. This model prescribes different probabilities for the presence of edges…

Machine Learning · Computer Science 2020-09-24 Alexander Jung

The enormous successes have been made by quantum algorithms during the last decade. In this paper, we combine the quantum random walk (QRW) with the problem of data clustering, and develop two clustering algorithms based on the one…

Machine Learning · Computer Science 2008-12-09 Qiang Li , Yan He , Jing-ping Jiang

A well-known cluster expansion, which leads to virial expansion for the free energy of low density systems, is modified in such a way that it becomes applicable to the description of condensed state of matter. To this end, the averaging of…

Statistical Mechanics · Physics 2018-12-21 G. S. Bokun , M. F. Holovko

The adhesive dynamics of a one-dimensional aggregating gas of point particles is rigorously described. The infinite hierarchy of kinetic equations for the distributions of clusters of nearest neighbours is shown to be equivalent to a system…

Statistical Mechanics · Physics 2009-10-31 L. Frachebourg , Ph. A. Martin , ; J. Piasecki

Many simple natural phenomena are characterized by complex motion that appears random at first glance, but that often displays underlying patterns and behavior that can be clustered in groups. The movement of small pieces of paper falling…

Data Analysis, Statistics and Probability · Physics 2022-10-10 Arthur A. B. Pessa , Matjaz Perc , Haroldo V. Ribeiro

We consider a stationary random field indexed by an increasing sequence of subsets of $\mathbb{Z}^d$ obeying a very broad geometrical assumption on how the sequence expands. Under certain mixing and local conditions, we show how the tail…

Probability · Mathematics 2022-01-19 Anders Rønn-Nielsen , Mads Stehr