Structured Sparse Modelling with Hierarchical GP

04/27/2017

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by   Danil Kuzin, et al.

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In this paper a new Bayesian model for sparse linear regression with a spatio-temporal structure is proposed. It incorporates the structural assumptions based on a hierarchical Gaussian process prior for spike and slab coefficients. We design an inference algorithm based on Expectation Propagation and evaluate the model over the real data.