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Description:: Sherlockian artwork by Norman Schatell
Creator:: Schatell, Norman
Contributed By:: University of Minnesota Libraries, Special Collections and Rare Books.
Last Updated:: 2018-11-30

Description:: We will recall the notions of F-polynomial, g-vector, and c-vector from Cluster Algebras IV and related works, along with their basic properties.
Creator:: Williams, Harold (The University of Texas at Austin)
Created:: 2015-06-01
Contributed By:: University of Minnesota, Institute for Mathematics and its Applications.
Last Updated:: 2018-06-19

Description:: This talk discusses multiple methods for clustering high-dimensional data, and explores the delicate balance between utilizing data density and data geometry. I will first present path-based spectral clustering, a novel approach which combines a density-based metric with graph-based clustering. This density-based path metric allows for fast algo...
Creator:: Little, Anna (The University of Utah)
Created:: 2020-10-27
Contributed By:: University of Minnesota, Institute for Mathematics and its Applications.
Last Updated:: 2022-04-22

Description:: We consider the problem of simplifying representations for networks, or large weighted directed graphs, by aggregating nodes and edges. Our approach is to view this problem as a clustering problem and incorporate features of the deterministic annealing algorithm in our computational solution. The novelty in our method includes a quantitative mea...
Creator:: Beck, Carolyn (University of Illinois at Urbana-Champaign)
Created:: 2015-10-21
Contributed By:: University of Minnesota, Institute for Mathematics and its Applications.
Last Updated:: 2018-06-19

Description:: Clustering is a stable phase-locked activity pattern that has been observed in networks of intrinsically oscillating neurons. In these states the network breaks up into clusters. Neurons within a cluster exhibit phase-locked behavior with zero phase-lag, while between clusters neurons are phase-locked with non-zero phase-lag. Clustering has been...
Creator:: Booth, Victoria (University of Michigan); Campbell, Sue Ann (University of Waterloo)
Created:: 2013-09-09
Contributed By:: University of Minnesota, Institute for Mathematics and its Applications.
Last Updated:: 2018-06-19

Description:: Over the past few years, various techniques have been developed for learning a low-dimensional representation of data lying in a nonlinear manifold embedded in a high-dimensional space. Unfortunately, most of these techniques are limited to the analysis of a single submanifold of a Euclidean space and suffer from degeneracies when applied to lin...
Creator:: Vidal, René (Johns Hopkins University)
Created:: 2008-10-28
Contributed By:: University of Minnesota, Institute for Mathematics and its Applications.
Last Updated:: 2018-06-19

Description:: To, effectively, combat the opioid epidemic and associated infectious diseases we must elucidate factors associated with therapeutic initiation, adherence and completion of therapy. However, the patient population compounds the problem of elucidation of these factors. Substance users are characterized by lack of medical care, generally limited f...
Creator:: Markatou, Marianthi (University at Buffalo (SUNY))
Created:: 2018-11-08
Contributed By:: University of Minnesota, Institute for Mathematics and its Applications.
Last Updated:: 2019-02-04

Description:: Given a set V of n elements, consider the simple task of clustering them into k clusters, where k is unknown. We are allowed to make pairwise queries. Given elements u and v in V, a query asks whether u,v belong to the same cluster and returns a binary answer assuming a true underlying clustering. The goal is to minimize the number of such queri...
Creator:: Mazumdar, Arya (University of Massachusetts)
Created:: 2016-10-28
Contributed By:: University of Minnesota, Institute for Mathematics and its Applications.
Last Updated:: 2018-06-19