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In this paper, we propose a natural notion of individual preference (IP) stability for clustering, which asks that every data point, on average, is closer to the points in its own cluster than to the points in any other cluster. Our notion…

In recent work, generalized persistence modules have proved useful in distinguishing noise from the legitimate topological features of a data set. Algebraically, generalized persistence modules can be viewed as representations for the poset…

Algebraic Topology · Mathematics 2017-10-10 Killian Meehan , David Meyer

This paper establishes a theoretical framework to describe the transition from consensus to stable clustering in multi-agent systems with nonlinear, cooperative interactions. We first establish a sharp threshold for consensus. For a broad…

Systems and Control · Electrical Eng. & Systems 2025-11-27 Anthony Couthures , Gustave Bainier , Vineeth Satheeskumar Varma , Samson Lasaulce , Irinel-Constantin Morarescu

We propose some axioms for hierarchical clustering of probability measures and investigate their ramifications. The basic idea is to let the user stipulate the clusters for some elementary measures. This is done without the need of any…

Machine Learning · Statistics 2016-05-24 Philipp Thomann , Ingo Steinwart , Nico Schmid

We have shown [J.\ Fluid Mech.\ {\bf 592}, 447 (2007)] that swapping (reversing) trajectories in confined suspension flows prevent collisions between particles approaching each other in adjacent streamlines. Here we demonstrate that by…

Soft Condensed Matter · Physics 2015-06-03 M. Zurita-Gotor , J. Bławzdziewicz , E. Wajnryb

Finding a set of nested partitions of a dataset is useful to uncover relevant structure at different scales, and is often dealt with a data-dependent methodology. In this paper, we introduce a general two-step methodology for model-based…

Computation · Statistics 2021-04-22 Etienne Côme , Nicolas Jouvin , Pierre Latouche , Charles Bouveyron

In many systems consisting of interacting subsystems, the complex interactions between elements can be represented using multilayer networks. However percolation, key to understanding connectivity and robustness, is not trivially…

Disordered Systems and Neural Networks · Physics 2020-11-04 G. J. Baxter , R. A. da Costa , S. N. Dorogovtsev , J. F. F. Mendes

The extended persistence diagram is an invariant of piecewise linear functions, which is known to be stable under perturbations of functions with respect to the bottleneck distance as introduced by Cohen-Steiner, Edelsbrunner, and Harer. We…

Algebraic Topology · Mathematics 2024-07-08 Ulrich Bauer , Magnus Bakke Botnan , Benedikt Fluhr

The problem of clustering noisy and incompletely observed high-dimensional data points into a union of low-dimensional subspaces and a set of outliers is considered. The number of subspaces, their dimensions, and their orientations are…

Machine Learning · Statistics 2015-08-24 Reinhard Heckel , Helmut Bölcskei

A layered system of two-dimensional planes containing fermionic polar molecules can potentially realize a number of exotic quantum many-body states. Among the predictions, are density-wave instabilities driven by the anisotropic part of the…

Quantum Gases · Physics 2015-03-18 N. T. Zinner , G. M. Bruun

We consider a generalized version of the correlation clustering problem, defined as follows. Given a complete graph $G$ whose edges are labeled with $+$ or $-$, we wish to partition the graph into clusters while trying to avoid errors: $+$…

Data Structures and Algorithms · Computer Science 2016-05-25 Gregory J. Puleo , Olgica Milenkovic

We provide a complete taxonomic characterization of robust hierarchical clustering methods for directed networks following an axiomatic approach. We begin by introducing three practical properties associated with the notion of robustness in…

Machine Learning · Computer Science 2021-08-21 Gunnar Carlsson , Facundo Mémoli , Santiago Segarra

There has been a surge in the number of large and flat data sets - data sets containing a large number of features and a relatively small number of observations - due to the growing ability to collect and store information in medical…

Machine Learning · Statistics 2017-07-05 Hongyang Zhang , Ruben H. Zamar

Geometrically, foams or covalent graphs can be decomposed into successive layers or strata. Disorder of the underlying structure imposes a characteristic roughening of the layers. Our main results are hysteresis and convergence in the layer…

Disordered Systems and Neural Networks · Physics 2007-05-23 C. Oguey , N. Rivier , T. Aste

A multilayered particle is illuminated by plane acoustic or electromagnetic waves of one or several frequencies. We consider the inverse scattering problem for the identification of the layers and of the refraction coefficients of the…

Mathematical Physics · Physics 2016-09-07 Semion Gutman

High dimensional data often contain multiple facets, and several clustering patterns can co-exist under different variable subspaces, also known as the views. While multi-view clustering algorithms were proposed, the uncertainty…

Machine Learning · Statistics 2019-10-09 Leo L Duan

Dirichlet process mixtures are flexible non-parametric models, particularly suited to density estimation and probabilistic clustering. In this work we study the posterior distribution induced by Dirichlet process mixtures as the sample size…

Statistics Theory · Mathematics 2022-11-29 Filippo Ascolani , Antonio Lijoi , Giovanni Rebaudo , Giacomo Zanella

Usual formulations of the clustering coefficient can be shown to be insufficient in the task of describing the local topology of very simple networks. Motivated by this, we review some alternatives in order to present an extension, the…

Data Analysis, Statistics and Probability · Physics 2007-05-23 Alexandre H. Abdo , A. P. S. de Moura

Agglomerative hierarchical clustering can be implemented with several strategies that differ in the way elements of a collection are grouped together to build a hierarchy of clusters. Here we introduce versatile linkage, a new infinite…

Methodology · Statistics 2021-03-26 Alberto Fernández , Sergio Gómez

Typically clustering algorithms provide clustering solutions with prespecified number of clusters. The lack of a priori knowledge on the true number of underlying clusters in the dataset makes it important to have a metric to compare the…

Machine Learning · Computer Science 2018-11-20 Amber Srivastava , Mayank Baranwal , Srinivasa Salapaka