Learning Graphical Models From the Glauber Dynamics
In this paper, we consider the problem of learning undirected graphical models from data generated according to the Glauber dynamics (also known as the Gibbs sampler). The Glauber dynamics is a Markov chain that sequentially updates individual nodes (variables) in a graphical model and it is frequen...
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| Format: | Article |
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Institute of Electrical and Electronics Engineers (IEEE)
2019
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| Online Access: | http://hdl.handle.net/1721.1/120526 https://orcid.org/0000-0003-1303-582X https://orcid.org/0000-0001-8898-8778 https://orcid.org/0000-0003-0737-3259 |