Editors:
- Includes supplementary material: sn.pub/extras
Part of the book series: Lecture Notes in Computer Science (LNCS, volume 9505)
Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)
Conference series link(s): AMBN: Workshop on Advanced Methodologies for Bayesian Networks
Conference proceedings info: AMBN 2015.
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Table of contents (18 papers)
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Front Matter
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Back Matter
About this book
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.
Keywords
- Causal inference
- Convex optimization
- Genetic algorithm
- Linear programming
- Naive bayes
- Algorithm selection
- Bayesian networks
- Classification consistency
- Clustering
- Consistency
- Data imputation
- Empirical hardness
- Gene differential analysis
- Logistic regression
- Multi-linear functions
- Mutual information
- Parameter learning
- RFID Data
- Robust inference
- Structure learning
Editors and Affiliations
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Osaka University, Osaka, Japan
Joe Suzuki
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The University of Electro-Communications, Tokyo, Japan
Maomi Ueno
Bibliographic Information
Book Title: Advanced Methodologies for Bayesian Networks
Book Subtitle: Second International Workshop, AMBN 2015, Yokohama, Japan, November 16-18, 2015. Proceedings
Editors: Joe Suzuki, Maomi Ueno
Series Title: Lecture Notes in Computer Science
DOI: https://doi.org/10.1007/978-3-319-28379-1
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer International Publishing Switzerland 2015
Softcover ISBN: 978-3-319-28378-4Published: 25 February 2016
eBook ISBN: 978-3-319-28379-1Published: 07 January 2016
Series ISSN: 0302-9743
Series E-ISSN: 1611-3349
Edition Number: 1
Number of Pages: XVIII, 265
Number of Illustrations: 102 illustrations in colour
Topics: Artificial Intelligence, Algorithm Analysis and Problem Complexity, Probability and Statistics in Computer Science, Computation by Abstract Devices, Database Management, Information Systems Applications (incl. Internet)