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» Compiling Bayesian Networks Using Variable Elimination
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ECAI
2004
Springer
14 years 25 days ago
Using Constraints with Memory to Implement Variable Elimination
Abstract. Adaptive consistency is a solving algorithm for constraint networks. Its basic step is variable elimination: it takes a network as input, and producesan equivalent networ...
Martí Sánchez, Pedro Meseguer, Javie...
CP
2006
Springer
13 years 11 months ago
Compiling Constraint Networks into AND/OR Multi-valued Decision Diagrams (AOMDDs)
Abstract. Inspired by AND/OR search spaces for graphical models recently introduced, we propose to augment Ordered Decision Diagrams with AND nodes, in order to capture function de...
Robert Mateescu, Rina Dechter
ICASSP
2011
IEEE
12 years 11 months ago
Gesture-based Dynamic Bayesian Network for noise robust speech recognition
Previously we have proposed different models for estimating articulatory gestures and vocal tract variable (TV) trajectories from synthetic speech. We have shown that when deploye...
Vikramjit Mitra, Hosung Nam, Carol Y. Espy-Wilson,...
IAT
2009
IEEE
13 years 11 months ago
Efficient Distributed Bayesian Reasoning via Targeted Instantiation of Variables
Abstract--This paper is focusing on exact Bayesian reasoning in systems of agents, which represent weakly coupled processing modules supporting collaborative inference through mess...
Patrick de Oude, Gregor Pavlin
JUCS
2006
87views more  JUCS 2006»
13 years 7 months ago
Eliminating Redundant Join-Set Computations in Static Single Assignment
: The seminal algorithm developed by Ron Cytron, Jeanne Ferrante and colleagues in 1989 for the placement of -nodes in a control flow graph is still widely used in commercial compi...
Angela French, José Nelson Amaral