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Bayesian Inference for Structured Spike and Slab Priors
Michael Riis Andersen · Ole Winther · Lars K Hansen

Wed Dec 10 04:00 PM -- 08:59 PM (PST) @ Level 2, room 210D #None

Sparse signal recovery addresses the problem of solving underdetermined linear inverse problems subject to a sparsity constraint. We propose a novel prior formulation, the structured spike and slab prior, which allows to incorporate a priori knowledge of the sparsity pattern by imposing a spatial Gaussian process on the spike and slab probabilities. Thus, prior information on the structure of the sparsity pattern can be encoded using generic covariance functions. Furthermore, we provide a Bayesian inference scheme for the proposed model based on the expectation propagation framework. Using numerical experiments on synthetic data, we demonstrate the benefits of the model.

Author Information

Michael Riis Andersen (Aalto University)
Ole Winther (Technical University of Denmark)
Lars K Hansen (Technical University of Denmark)

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