Affinity Propagation Outlier Clustering10/04/2017 Objective: Inspiration In this paper I present an extension of affinity propagation which simultaneously clusters and detects outliers in data. The advantagesinclude: (i) the resulting clusters tend to be compact and semantically coherent (ii) the clusters are more robust against data perturbations and (iii) the outliers are contextualized by the clusters and are more interpretable. Speaker(s)
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