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» Compiling Bayesian Networks Using Variable Elimination
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ECSQARU
2005
Springer
14 years 2 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»
14 years 2 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
13 years 10 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
13 years 10 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
14 years 21 days 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,...