Learning Graphical Models From the Glauber Dynamics

Learning Graphical Models From the Glauber Dynamics

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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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Bibliographic Details
Main Authors: Bresler, Guy (Contributor), Gamarnik, David (Contributor), Shah, Devavrat (Contributor)
Other Authors: Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science (Contributor), Massachusetts Institute of Technology. Laboratory for Information and Decision Systems (Contributor), Sloan School of Management (Contributor)
Format: Article
Language:English
Published: Institute of Electrical and Electronics Engineers (IEEE), 2019-02-21T19:01:07Z.
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