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Related papers: Cluster equivalence and graded derived equivalence

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Holm and Jorgensen have shown the existence of a cluster structure on a certain category $D$ that shares many properties with finite type $A$ cluster categories and that can be fruitfully considered as an infinite analogue of these. In this…

Representation Theory · Mathematics 2014-12-03 Jan E. Grabowski , Sira Gratz

We provide a classification of generalized tilting modules and full exceptional sequences for the dual extension algebra of the path algebra of a uniformly oriented linear quiver modulo the ideal generated by paths of length two with its…

Representation Theory · Mathematics 2022-04-01 Elin Persson Westin , Markus Thuresson

Neural network-based clustering has recently gained popularity, and in particular a constrained clustering formulation has been proposed to perform transfer learning and image category discovery using deep learning. The core idea is to…

Computer Vision and Pattern Recognition · Computer Science 2018-06-29 Yen-Chang Hsu , Zhaoyang Lv , Joel Schlosser , Phillip Odom , Zsolt Kira

We study the cluster category of a canonical algebra A in terms of the hereditary category of coherent sheaves over the corresponding weighted projective line X. As an application we determine the automorphism group of the cluster category…

Representation Theory · Mathematics 2020-09-28 Michael Barot , Dirk Kussin , Helmut Lenzing

Classification and clustering have been studied separately in machine learning and computer vision. Inspired by the recent success of deep learning models in solving various vision problems (e.g., object recognition, semantic segmentation)…

Machine Learning · Computer Science 2017-12-13 Ali Borji , Aysegul Dundar

A computational theory for clustering and a semi-supervised clustering algorithm is presented. Clustering is defined to be the obtainment of groupings of data such that each group contains no anomalies with respect to a chosen grouping…

Machine Learning · Computer Science 2025-07-17 Nassir Mohammad

We study the module category of a certain Galois covering of a cluster-tilted algebra which we call the cluster repetitive algebra. Our main result compares the module categories of the cluster repetitive algebra of a tilted algebra C and…

Representation Theory · Mathematics 2007-09-07 Ibrahim Assem , Thomas Bruestle , Ralf Schiffler

We first study a new family of graded quiver varieties together with a new $t$-deformation of the associated Grothendieck rings. This provides the geometric foundations for a joint paper by Yoshiyuki Kimura and the author. We further…

Quantum Algebra · Mathematics 2016-06-22 Fan Qin

The applicability of agglomerative clustering, for inferring both hierarchical and flat clustering, is limited by its scalability. Existing scalable hierarchical clustering methods sacrifice quality for speed and often lead to over-merging…

Traditionally, clustering algorithms focus on partitioning the data into groups of similar instances. The similarity objective, however, is not sufficient in applications where a fair-representation of the groups in terms of protected…

Machine Learning · Computer Science 2021-11-08 Tai Le Quy , Arjun Roy , Gunnar Friege , Eirini Ntoutsi

The purpose of this paper is to give an explicit formula for the number of non-isomorphic cluster-tilted algebras of type $A_n$, by counting the mutation class of any quiver with underlying graph $A_n$. It will also follow that if $T$ and…

Representation Theory · Mathematics 2008-04-16 Hermund André Torkildsen

We present a combinatorial model for cluster algebras of type $D_n$ in terms of centrally symmetric pseudotriangulations of a regular $2n$-gon with a small disk in the centre. This model provides convenient and uniform interpretations for…

Commutative Algebra · Mathematics 2023-11-14 Cesar Ceballos , Vincent Pilaud

Clustering is a well-known unsupervised machine learning approach capable of automatically grouping discrete sets of instances with similar characteristics. Constrained clustering is a semi-supervised extension to this process that can be…

Machine Learning · Computer Science 2023-03-02 Germán González-Almagro , Daniel Peralta , Eli De Poorter , José-Ramón Cano , Salvador García

Data clustering is the process of identifying natural groupings or clusters within multidimensional data based on some similarity measure. Clustering is a fundamental process in many different disciplines. Hence, researchers from different…

Machine Learning · Computer Science 2014-08-26 Sibei Yang , Liangde Tao , Bingchen Gong

We show that for two quivers without oriented cycles related by a BGP reflection, the posets of their cluster tilting objects are related by a simple combinatorial construction, which we call a flip-flop. We deduce that the posets of…

Representation Theory · Mathematics 2007-10-16 Sefi Ladkani

Clustering algorithms are one of the main analytical methods to detect patterns in unlabeled data. Existing clustering methods typically treat samples in a dataset as points in a metric space and compute distances to group together similar…

Machine Learning · Computer Science 2021-10-12 Tarek Naous , Srinjay Sarkar , Abubakar Abid , James Zou

We describe the upper seminormal crystal structure for the $\mu$-supported $\delta$-vectors for any quiver with potential with reachable frozen vertices, or equivalently for the tropical points of the corresponding cluster $\mc{X}$-variety.…

Representation Theory · Mathematics 2024-12-17 Jiarui Fei

We prove that mutation of cluster-tilting objects in triangulated 2-Calabi-Yau categories is closely connected with mutation of quivers with potentials. This gives a close connection between 2-CY-tilted algebras and Jacobian algebras…

Representation Theory · Mathematics 2012-10-30 Aslak Bakke Buan , Osamu Iyama , Idun Reiten , David Smith

We give a complete derived equivalence classification of all symmetric algebras of domestic representation type over an algebraically closed field. This completes previous work by R. Bocian and the authors, where in this paper we solve the…

Representation Theory · Mathematics 2007-05-23 Thorsten Holm , Andrzej Skowronski

In cancer research, clustering techniques are widely used for exploratory analyses and dimensionality reduction, playing a critical role in the identification of novel cancer subtypes, often with direct implications for patient management.…