The Hidden Life of Latent Variables: Bayesian Learning with Mixed Graph Models

Abstract

Directed acyclic graphs (DAGs) have been widely used as a representation of conditional independence in machine learning and statistics. Moreover, hidden or latent variables are often an important component of graphical models. However, DAG models suffer from an important limitation: the family of DAGs is not closed under marginalization of hidden variables… (More)
DOI: 10.1145/1577069.1577110

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Cite this paper

@article{Silva2009TheHL, title={The Hidden Life of Latent Variables: Bayesian Learning with Mixed Graph Models}, author={Ricardo Bezerra de Andrade e Silva and Zoubin Ghahramani}, journal={Journal of Machine Learning Research}, year={2009}, volume={10}, pages={1187-1238} }