Nonparametric Belief Propagation.

Continuous quantities are ubiquitous in models of real-world phenomena, but are surprisingly difficult to reason about automatically. Probabilistic graphical models such as Bayesian networks and Markov random fields, and algorithms for approximate inference such as belief propagation (BP), have prov...

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Detalles Bibliográficos

Publicado en:	Communications of the ACM Vol. 53; no. 10; pp. 95 - 104
Autores principales:	Sudderth, Erik B., Ihler, Alexander T., Isard, Michael, Freeman, William T., Willsky, Alan S.
Formato:	Artículo
Publicado:	Association for Computing Machinery Oct2010
Materias:	Information modeling Nonparametric statistics Kinematics Localization theory Sensor networks Probability theory Graphical modeling (Statistics)
Acceso en línea:	Ver este registro en EBSCOhost