TY  - BOOK
AU  - Suzuki,Joe
AU  - Ueno,Maomi
ED  - International Workshop on Advanced Methodologies for Bayesian Networks
TI  - Advanced methodologies for Bayesian networks: second international workshop, AMBN 2015, Yokohama, Japan, November 16-18, 2015. Proceedings 
T2  - Lecture notes in artificial intelligence,
SN  - 9783319283791
AV  - Q334 
U1  - 006.3 23
PY  - 2015///
CY  - Cham
PB  - Springer
KW  - Artificial intelligence
KW  - Congresses
KW  - Bayesian statistical decision theory
KW  - Intelligence artificielle
KW  - Congrès
KW  - Théorie de la décision bayésienne
KW  - Algorithms & data structures
KW  - bicssc
KW  - Maths for computer scientists
KW  - User interface design & usability
KW  - Databases
KW  - Information retrieval
KW  - Computers
KW  - Programming
KW  - Algorithms
KW  - bisacsh
KW  - Mathematical & Statistical Software
KW  - Machine Theory
KW  - Database Management
KW  - General
KW  - Information Technology
KW  - Intelligence (AI) & Semantics
KW  - fast
KW  - Congress
KW  - proceedings (reports)
KW  - aat
KW  - Conference papers and proceedings
KW  - lcgft
KW  - Actes de congrès
KW  - rvmgf
N1  - International conference proceedings; Includes author index; Effectiveness of graphical models including modeling. Reasoning, model selection -- Logic-probability relations -- Causality. Applying graphical models in real world settings -- Scalability -- Incremental learning.-Parallelization
N2  - 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
UR  - https://link.springer.com/10.1007/978-3-319-28379-1
ER  -