… In this section, the Thomas process and the Cauchy cluster process are applied to model
the long-leaf pine data-set. Figure 1 shows the locations of 584 long-leaf pine trees, as …

… Based on the Cauchy distribution, we design a Cauchy kernel … influence is redefined based
on Cauchy kernel. This criterion … 1 shows the peeling process and the clustering results of the …

… The method is based on clustering and a simple Cauchy mutation. The results obtained on
a broad … of the whole clustering process may be estimated as O ( N P · ( t m a x · k · d + 1 ) ) . …

… this paper, we propose a subspace clustering method based on Cauchy loss function (CLF). …
role in the process of subspace clustering. Therefore, most spectral clustering-based …

… This paper is organized as follows: after the introduction, the basics of Cauchy density of a
… used in data stream processing and the recursive computation of cluster covariance matrix is …

… with the spatial trend and clustering patterns. In particular, the … In this study, we consider
the Cauchy cluster process with … -linear model, the Cauchy cluster process with a log-additive …

… Cauchy possibilistic clustering for data in the same cluster… processing time of the proposed
model are investigated and compared with the recent works on possibilistic Cauchy clustering…

… of an infinite cluster because these graphs almost surely have infinitely many cut-points,
we exhibit a phase transition at p = 1/2 for the size distribution of the origin cluster. More …

… processes is the square of the Hellinger distance between their respective intensity
measures. The Poisson point process … We illustrate the use of our result on the Cauchy-Schwarz …

… evolving Cauchy possibilistic clustering (eCauchy). The idea of density based clustering is
… The development of density as a measure of similarity follows from Cauchy density and is …