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» Compiling Bayesian Networks Using Variable Elimination
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ECSQARU
2005
Springer
15 years 7 months ago
Nonlinear Deterministic Relationships in Bayesian Networks
In a Bayesian network with continuous variables containing a variable(s) that is a conditionally deterministic function of its continuous parents, the joint density function for t...
Barry R. Cobb, Prakash P. Shenoy
ICMCS
2006
IEEE
117views Multimedia» more  ICMCS 2006»
15 years 8 months ago
Soccer Highlight Detection using Two-Dependence Bayesian Network
Soccer highlight detection is an active research topic in recent years. One of the difficult problems is how to effectively fuse multi-modality cues, i.e. audio, visual and textu...
Jianguo Li, Tao Wang, Wei Hu, Mingliang Sun, Yimin...
IJCAI
2007
15 years 3 months ago
Compiling Bayesian Networks by Symbolic Probability Calculation Based on Zero-Suppressed BDDs
Compiling Bayesian networks (BNs) is one of the hot topics in the area of probabilistic modeling and processing. In this paper, we propose a new method of compiling BNs into multi...
Shin-ichi Minato, Ken Satoh, Taisuke Sato
BIRTHDAY
2008
Springer
15 years 4 months ago
AND/OR Multi-valued Decision Diagrams for Constraint Networks
The paper is an overview of a recently developed compilation data structure for graphical models, with specific application to constraint networks. The AND/OR Multi-Valued Decision...
Robert Mateescu, Rina Dechter
PLDI
1996
ACM
15 years 6 months ago
Fast, Effective Dynamic Compilation
Dynamic compilation enables optimizations based on the values of invariant data computed at run-time. Using the values of these runtime constants, a dynamic compiler can eliminate...
Joel Auslander, Matthai Philipose, Craig Chambers,...