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Related papers: On I-statistical cluster point of double sequences

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We define several notions of a limit point on sequences with domain a barrier in $[\omega]^{<\omega}$ focusing on the two dimensional case $[\omega]^2$. By exploring some natural candidates, we show that countable compactness has a number…

General Topology · Mathematics 2024-06-26 Cesar Corral , Pourya Memarpanahi , Paul Szeptycki

This is the second of two closely related papers on transversality. Here we introduce the notion of strong tangential transversality of two closed subsets of a Banach space which is a natural sufficient condition for tangential…

Optimization and Control · Mathematics 2018-10-09 Mira Bivas , Mikhail Krastanov , Nadezhda Ribarska

The concept of statistical convergence based on asymptotic density is introduced in this article through nets. Some possible extensions of classical results for statistical convergence of sequences are obtained in this article, with…

General Topology · Mathematics 2019-07-02 AR. Murugan , J. Dianavinnarasi , C. Ganesa Moorthy

We define a class of so-called thinnable ideals $\mathcal{I}$ on the positive integers which includes several well-known examples, e.g., the collection of sets with zero asymptotic density, sets with zero logarithmic density, and several…

Classical Analysis and ODEs · Mathematics 2018-02-05 Paolo Leonetti

We study diagonal multipoint Pad\'e approximants to sums of a Cauchy transform of a complex measure and a rational function. The measure is assumed to have compact regular support included into the real line and an argument of bounded…

Classical Analysis and ODEs · Mathematics 2009-06-04 L. Baratchart , M. Yattselev

The main object of this paper is to investigate $\lambda$-statistically quasi-Cauchy sequences. A real valued function $f$ defined on a subset $E$ of $\textbf{R}$, the set of real numbers, is called $\lambda$-statistically ward continuous…

General Mathematics · Mathematics 2013-07-23 Huseyin Cakalli , Ayse Sonmez , Cigdem Gunduz Aras

The idea underlying the modal formulation of density-based clustering is to associate groups with the regions around the modes of the probability density function underlying the data. This correspondence between clusters and dense regions…

Social and Information Networks · Computer Science 2021-01-22 Giovanna Menardi , Domenico De Stefano

Cluster analysis is a fundamental research issue in statistics and machine learning. In many modern clustering methods, we need to determine whether two subsets of samples come from the same cluster. Since these subsets are usually…

Machine Learning · Computer Science 2025-07-15 Xinying Liu , Lianyu Hu , Mudi Jiang , Simeng Zhang , Jun Lou , Zengyou He

In this paper we address the global stability problem for double-bubbles in the plane. This is accomplished by combining the "improved convergence theorem" for planar clusters developed in arXiv:1409.6652 with an ad hoc analysis of the…

Analysis of PDEs · Mathematics 2015-04-23 Marco Cicalese , Gian Paolo Leonardi , Francesco Maggi

We consider a slow diffusion equation with a singular quenching term, extending the mathematical treatment made in 1992 by B. Kawohl and R. Kersner for the one-dimensional case. Besides the existence of a very weak solution, we prove some…

Analysis of PDEs · Mathematics 2020-01-29 Nguyen Anh Dao , Jesús Ildefonso Díaz , Quan Ba Hong Nguyen

After generalizing the concept of clusters to incorporate clusters that are linked to other clusters through some relatively narrow bridges, an approach for detecting patches of separation between these clusters is developed based on an…

Computer Vision and Pattern Recognition · Computer Science 2020-01-10 Luciano da F. Costa

The statistical convergence is defined for sequences with the asymptotic density on the natural numbers, in general. In this paper, we introduce the statistical convergence for nets in Riesz spaces by using the finite additive measures on…

Functional Analysis · Mathematics 2021-05-19 Abdullah Aydın , Fatih Temizsu

In this paper, using the concept of ideal, we study the idea of rough ideal convergence of sequences which is an extension of the notion of rough convergence of sequences in a partial metric space. We define the set of rough…

General Topology · Mathematics 2025-01-15 Sukila Khatun , Amar Kumar Banerjee , Rahul Mondal

Clustering is widely studied in statistics and machine learning, with applications in a variety of fields. As opposed to classical algorithms which return a single clustering solution, Bayesian nonparametric models provide a posterior over…

Methodology · Statistics 2019-02-11 Sara Wade , Zoubin Ghahramani

In this paper we will characterize the completeness and barrelledness of a normed space through the strong p-Ces\`aro summability of series. A new characterization of weakly unconditionally Cauchy series and unconditionally convergent…

Functional Analysis · Mathematics 2024-02-12 Fernando León-Saavedra , Soledad Moreno-Pulido , Antonio Sala-Pérez

An ideal $I$ is a family of subsets of positive integers $\textbf{N}$ which is closed under taking finite unions and subsets of its elements. A sequence $(x_n)$ of real numbers is said to be $I$-convergent to a real number $L$, if for each…

General Mathematics · Mathematics 2012-03-12 Huseyin Cakalli , Bipan Hazarika

This article is devoted to extend the "$\eps-\eps^\beta$ property" to the case of clusters in an Euclidean space with a double density.

Analysis of PDEs · Mathematics 2025-10-10 A. Pratelli , V. Scattaglia

Let $\mathcal{C}$ be a Hom-finite triangulated 2-Calabi-Yau category with a cluster tilting object. Under some constructibility assumptions on $\mathcal{C}$ which are satisfied for instance by cluster categories, by generalized cluster…

Representation Theory · Mathematics 2014-02-26 Yann Palu

In this article we introduce associative Look-Up Tables. With their help, pseudo sums are correctly determined. The set of limit distributions in a pseudo-summation scheme of i.i.d. random variables is described. Also, two special cases…

Probability · Mathematics 2023-06-02 Ivan Alexeev , Ignat Melnikov , Artem Uglovski

Sum-of-norms clustering is a popular convexification of $K$-means clustering. We show that, if the dataset is made of a large number of independent random variables distributed according to the uniform measure on the union of two disjoint…

Machine Learning · Computer Science 2024-05-15 Alexander Dunlap , Jean-Christophe Mourrat