Parsimonious modeling with Information Filtering Networks

23 Feb 2016Wolfram BarfussGuido Previde MassaraT. Di MatteoTomaso Aste

We introduce a methodology to construct parsimonious probabilistic models. This method makes use of Information Filtering Networks to produce a robust estimate of the global sparse inverse covariance from a simple sum of local inverse covariances computed on small sub-parts of the network... (read more)

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