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Cluster analysis requires many decisions: the clustering method and the implied reference model, the number of clusters and, often, several hyper-parameters and algorithms' tunings. In practice, one produces several partitions, and a final…

Machine Learning · Statistics 2023-08-14 Luca Coraggio , Pietro Coretto

We give a combinatorial intepretation of cluster variables of a specific cluster algebra under a mutation sequence of period 6, in terms of perfect matchings of subgraphs of the brane tiling dual to the quiver associated with the cluster…

Combinatorics · Mathematics 2015-11-20 Sicong Zhang

Let T be a tilting object in a triangulated category equivalent to the bounded derived category of a hereditary abelian category with finite dimensional homomorphism spaces and split idempotents. This text investigates the strong global…

Representation Theory · Mathematics 2017-03-17 Edson Ribeiro Alvares , Patrick Le Meur , Eduardo N. Marcos

Clustering is an unsupervised learning problem that aims to partition unlabelled data points into groups with similar features. Traditional clustering algorithms provide limited insight into the groups they find as their main focus is…

Machine Learning · Computer Science 2022-10-18 Connor Lawless , Oktay Gunluk

We study the deformation theory of the Stanley-Reisner rings associated to cluster complexes for skew-symmetrizable cluster algebras of geometric and finite cluster type. In particular, we show that in the skew-symmetric case, these cluster…

Algebraic Geometry · Mathematics 2025-03-03 Nathan Ilten , Alfredo Nájera Chávez , Hipolito Treffinger

LP algebras, introduced by Lam and Pylyavskyy, are a generalization of cluster algebras. These algebras are known to have the Laurent phenomenon, but positivity remains conjectural. Graph LP algebras are finite LP algebras encoded by a…

Combinatorics · Mathematics 2022-11-28 Esther Banaian , Sunita Chepuri , Elizabeth Kelley , Sylvester W. Zhang

Many clustering schemes are defined by optimizing an objective function defined on the partitions of the underlying set of a finite metric space. In this paper, we construct a framework for studying what happens when we instead impose…

Machine Learning · Statistics 2010-12-01 Gunnar Carlsson , Facundo Memoli

In this work, we introduce a novel methodology for divisive hierarchical clustering. Our divisive (``top-down'') approach is motivated by the fact that agglomerative hierarchical clustering (``bottom-up''), which is commonly used for…

Methodology · Statistics 2025-10-07 Jan O. Bauer

This paper studies cluster algebras locally, by identifying a special class of localizations which are themselves cluster algebras. A `locally acyclic cluster algebra' is a cluster algebra which admits a finite cover (in a geometric sense)…

Algebraic Geometry · Mathematics 2014-05-19 Greg Muller

We initiate a systematic study of the cohomology of cluster varieties. We introduce the Louise property for cluster algebras that holds for all acyclic cluster algebras, and for most cluster algebras arising from marked surfaces. For…

Algebraic Geometry · Mathematics 2022-03-09 Thomas Lam , David E. Speyer

This paper continues the study of cluster algebras initiated in math.RT/0104151. Its main result is the complete classification of the cluster algebras of finite type, i.e., those with finitely many clusters. This classification turns out…

Rings and Algebras · Mathematics 2015-06-26 Sergey Fomin , Andrei Zelevinsky

Q-systems first appeared in the analysis of the Bethe equations for the XXX-model and generalized Heisenberg spin chains. Such systems are known to exist for any simple Lie algebra and many other Kac-Moody algebras. We formulate the…

Representation Theory · Mathematics 2008-11-26 Rinat Kedem

Let $\mathcal{H}$ be a connected hereditary abelian category with tilting objects. It is proved that the cluster-tilting graph associated with $\mathcal{H}$ is always connected. As a consequence, we establish the connectedness of the…

Representation Theory · Mathematics 2021-04-20 Changjian Fu , Shengfei Geng

We construct a representation of the braid groups in a cluster C*-algebra coming from a triangulation of the Riemann surface S with one or two cusps. It is shown that the Laurent polynomials attached to the K-theory of such an algebra are…

Operator Algebras · Mathematics 2016-03-04 Igor Nikolaev

A word over an ordered alphabet is said to be clustering if identical letters appear adjacently in its Burrows-Wheeler transform. Such words are strictly related to (discrete) interval exchange transformations. We use an extended version of…

Formal Languages and Automata Theory · Computer Science 2025-04-28 Francesco Dolce , Christian B. Hughes

We introduce a framework for $\mathbb{Z}$-gradings on cluster algebras (and their quantum analogues) that are compatible with mutation. To do this, one chooses the degrees of the (quantum) cluster variables in an initial seed subject to a…

Quantum Algebra · Mathematics 2014-12-03 Jan E. Grabowski , Stéphane Launois

We prove a multiplication formula for cluster characters induced by generating extensions in a gentle algebra A, generalizing a result of Cerulli Irelli, Esposito, Franzen, Reineke. In the case where A is the gentle algebra of a…

Representation Theory · Mathematics 2025-09-09 Azzurra Ciliberti

We consider a novel clustering task in which clusters can have compositional relationships, e.g., one cluster contains images of rectangles, one contains images of circles, and a third (compositional) cluster contains images with both…

Machine Learning · Computer Science 2023-08-04 Zeqian Li , Xinlu He , Jacob Whitehill

We introduce a new category C, which we call the cluster category, obtained as a quotient of the bounded derived category D of the module category of a finite-dimensional hereditary algebra H over a field. We show that, in the simply-laced…

Representation Theory · Mathematics 2020-12-21 Aslak Bakke Buan , Bethany Marsh , Markus Reineke , Idun Reiten , Gordana Todorov

This paper introduces a new clustering technique, called {\em dimensional clustering}, which clusters each data point by its latent {\em pointwise dimension}, which is a measure of the dimensionality of the data set local to that point.…

Machine Learning · Statistics 2018-05-29 Shohei Hidaka , Neeraj Kashyap
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