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Structured Sparse Modelling with Hierarchical GP
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.Comment: SPARS 201
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