Kuzin, D., Isupova, O. and Mihaylova, L. orcid.org/0000-0001-5856-2223 (Submitted: 2017) Structured Sparse Modelling with Hierarchical GP. arXiv. (Submitted)
Abstract
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.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2017 The Author(s) |
Keywords: | stat.ML; stat.ML |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield) |
Funding Information: | Funder Grant number EUROPEAN COMMISSION - FP6/FP7 TRAX - 607400 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 06 Jun 2017 09:31 |
Last Modified: | 06 Jun 2017 09:31 |
Published Version: | https://arxiv.org/abs/1704.08727 |
Status: | Submitted |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:116275 |