Bayesian inference for spatio-temporal spike-and-slab priors

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dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en Andersen, Michael Riis Vehtari, Aki Winther, Ole Kai Hansen, Lars 2018-08-01T13:29:20Z 2018-08-01T13:29:20Z 2017-12-01
dc.identifier.citation Andersen , M R , Vehtari , A , Winther , O & Kai Hansen , L 2017 , ' Bayesian inference for spatio-temporal spike-and-slab priors ' Journal of Machine Learning Research , vol 18 , pp. 1-58 . en
dc.identifier.issn 1532-4435
dc.identifier.issn 1533-7928
dc.identifier.other PURE UUID: 73d5d4ea-2270-4488-b674-59da8d3e3e0a
dc.identifier.other PURE ITEMURL:
dc.identifier.other PURE LINK:
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dc.description.abstract In this work, we address the problem of solving a series of underdetermined linear inverse problemblems subject to a sparsity constraint. We generalize the spike-and-slab prior distribution to encode a priori correlation of the support of the solution in both space and time by imposing a transformed Gaussian process on the spike-and-slab probabilities. An expectation propagation (EP) algorithm for posterior inference under the proposed model is derived. For large scale problems, the standard EP algorithm can be prohibitively slow. We therefore introduce three different approximation schemes to reduce the computational complexity. Finally, we demonstrate the proposed model using numerical experiments based on both synthetic and real data sets. en
dc.format.extent 1-58
dc.format.mimetype application/pdf
dc.language.iso en en
dc.relation.ispartofseries Journal of Machine Learning Research en
dc.relation.ispartofseries Volume 18 en
dc.rights openAccess en
dc.subject.other Software en
dc.subject.other Control and Systems Engineering en
dc.subject.other Statistics and Probability en
dc.subject.other Artificial Intelligence en
dc.subject.other 113 Computer and information sciences en
dc.title Bayesian inference for spatio-temporal spike-and-slab priors en
dc.type A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä fi
dc.description.version Peer reviewed en
dc.contributor.department Department of Computer Science
dc.contributor.department Technical University of Denmark
dc.subject.keyword Bayesian inference
dc.subject.keyword Expectation propagation
dc.subject.keyword Linear inverse problems
dc.subject.keyword Sparsity-promoting priors
dc.subject.keyword Spike-and-slab priors
dc.subject.keyword Software
dc.subject.keyword Control and Systems Engineering
dc.subject.keyword Statistics and Probability
dc.subject.keyword Artificial Intelligence
dc.subject.keyword 113 Computer and information sciences
dc.identifier.urn URN:NBN:fi:aalto-201808014213
dc.type.version publishedVersion

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