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Replicator Graph Clustering
2013
Procedings of the British Machine Vision Conference 2013
In this paper we introduce an efficient, effective and scalable clustering method denoted as Replicator Graph Clustering. Our method takes measures of similarity between pairs of data points (i. e. an affinity matrix) as input and identifies a set of clusters and unique cluster assignments in a fully unsupervised manner, where the cluster granularity is adaptable by a single parameter. We provide clustering results in three subsequent steps: (a) diffusing affinities by finding personalized
doi:10.5244/c.27.38
dblp:conf/bmvc/Donoser13
fatcat:xsbyxqkdfneyrey4mfcfls7qwm