Advanced Methodologies for Bayesian Networks Second International Workshop, AMBN 2015, Yokohama, Japan, November 16-18, 2015. Proceedings /

This volume constitutes the refereed proceedings of the Second International Workshop on Advanced Methodologies for Bayesian Networks, AMBN 2015, held in Yokohama, Japan, in November 2015. The 18 revised full papers and 6 invited abstracts presented were carefully reviewed and selected from numerous...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor Corporativo: SpringerLink (Online service)
Otros Autores: Suzuki, Joe (Editor ), Ueno, Maomi (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Cham : Springer International Publishing : Imprint: Springer, 2015.
Edición:1st ed. 2015.
Colección:Lecture Notes in Artificial Intelligence, 9505
Temas:
Artificial intelligence.
Algorithms.
Computer science-Mathematics.
Mathematical statistics.
Computer science.
Database management.
Application software.
Artificial Intelligence.
Probability and Statistics in Computer Science.
Theory of Computation.
Database Management.
Computer and Information Systems Applications.
Acceso en línea:Texto Completo
Descripción
Sumario:This volume constitutes the refereed proceedings of the Second International Workshop on Advanced Methodologies for Bayesian Networks, AMBN 2015, held in Yokohama, Japan, in November 2015. The 18 revised full papers and 6 invited abstracts presented were carefully reviewed and selected from numerous submissions. In the International Workshop on Advanced Methodologies for Bayesian Networks (AMBN), the researchers explore methodologies for enhancing the effectiveness of graphical models including modeling, reasoning, model selection, logic-probability relations, and causality. The exploration of methodologies is complemented discussions of practical considerations for applying graphical models in real world settings, covering concerns like scalability, incremental learning, parallelization, and so on.
Descripción Física:XVIII, 265 p. 102 illus. in color. online resource.
ISBN:9783319283791
ISSN:2945-9141 ;

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