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UAI
2004
13 years 8 months ago
An Empirical Evaluation of Possible Variations of Lazy Propagation
As real-world Bayesian networks continue to grow larger and more complex, it is important to investigate the possibilities for improving the performance of existing algorithms of ...
Andres Madsen
DIS
2009
Springer
13 years 10 months ago
Discovering Influential Nodes for SIS Models in Social Networks
We address the problem of efficiently discovering the influential nodes in a social network under the susceptible/infected/susceptible (SIS) model, a diffusion model where nodes ar...
Kazumi Saito, Masahiro Kimura, Hiroshi Motoda
UAI
1997
13 years 8 months ago
Exploring Parallelism in Learning Belief Networks
It has been shown that a class of probabilistic domain models cannot be learned correctly by several existing algorithms which employ a single-link lookahead search. When a multil...
Tongsheng Chu, Yang Xiang
VLSID
2006
IEEE
129views VLSI» more  VLSID 2006»
14 years 7 months ago
A Stimulus-Free Probabilistic Model for Single-Event-Upset Sensitivity
With device size shrinking and fast rising frequency ranges, effect of cosmic radiations and alpha particles known as Single-Event-Upset (SEU), Single-Eventtransients (SET), is a ...
Mohammad Gh. Mohammad, Laila Terkawi, Muna Albasma...
ROMAN
2007
IEEE
179views Robotics» more  ROMAN 2007»
14 years 1 months ago
A Bayesian Network Framework for Vision Based Semantic Scene Understanding
— For a robot to understand a scene, we have to infer and extract meaningful information from vision sensor data. Since scene understanding consists in recognizing several visual...
Seung-Bin Im, Keum-Sung Hwang, Sung-Bae Clio