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A Gibbs Sampler for Learning DAGs

We propose a Gibbs sampler for structure learning in directed acyclic graph (DAG) models. The standard Markov chain Monte Carlo algorithms used for learning DAGs are random-walk Metropolis-Hastings samplers. These samplers are guaranteed to converge asymptotically but often mix slowly when exploring...

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Detalles Bibliográficos
Publicado en:J Mach Learn Res
Main Authors: Goudie, Robert J. B., Mukherjee, Sach
Formato: Artigo
Idioma:Inglês
Publicado: 2016
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Acceso en liña:https://ncbi.nlm.nih.gov/pmc/articles/PMC5358773/
https://ncbi.nlm.nih.gov/pubmed/28331463
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