Automatic Dimension Selection for a Non-negative Factorization Approach to Clustering Multiple Random Graphs

24 Jun 2014  ·  Nam H. Lee, I-Jeng Wang, Youngser Park, Care E. Priebe, Michael Rosen ·

We consider a problem of grouping multiple graphs into several clusters using singular value thesholding and non-negative factorization. We derive a model selection information criterion to estimate the number of clusters. We demonstrate our approach using "Swimmer data set" as well as simulated data set, and compare its performance with two standard clustering algorithms.

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