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Conference item

Sparse nested Markov models with log-linear parameters

Abstract:

Hidden variables are ubiquitous in practical data analysis, and therefore modeling marginal densities and doing inference with the resulting models is an important problem in statistics, machine learning, and causal inference. Recently, a new type of graphical model, called the nested Markov model, was developed which captures equality constraints found in marginals of directed acyclic graph (DAG) models. Some of these constraints, such as the so called 'Verma constraint', strictly generalize...

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Pages:
576-585
Host title:
Uncertainty in Artificial Intelligence - Proceedings of the 29th Conference, UAI 2013
Publication date:
2013-01-01
Source identifiers:
454733
Pubs id:
pubs:454733
UUID:
uuid:a7ae93ce-0137-4258-a1c6-59bce6d18858
Local pid:
pubs:454733
Deposit date:
2014-10-20

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