A Bayesian Approach to Sparse plus Low rank Network Identification

Published 25 Mar 2015 in math.OC and stat.ML | (1503.07340v2)

Abstract: We consider the problem of modeling multivariate time series with parsimonious dynamical models which can be represented as sparse dynamic Bayesian networks with few latent nodes. This structure translates into a sparse plus low rank model. In this paper, we propose a Gaussian regression approach to identify such a model.

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