204 search results - page 17 / 41 » Learning locally minimax optimal Bayesian networks |
93
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GECCO
2008
Springer
14 years 10 months ago
2008
Springer
The key ideas behind most of the recently proposed Markov networks based EDAs were to factorise the joint probability distribution in terms of the cliques in the undirected graph....
74
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KDD
2003
ACM
15 years 10 months ago
2003
ACM
Data Mining with Bayesian Network learning has two important characteristics: under broad conditions learned edges between variables correspond to causal influences, and second, f...
100
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UAI
2008
14 years 11 months ago
2008
In this paper we introduce Refractor Importance Sampling (RIS), an improvement to reduce error variance in Bayesian network importance sampling propagation under evidential reason...
93
Voted
ECAI
2008
Springer
14 years 11 months ago
2008
Springer
Many real-world applications of AI require both probability and first-order logic to deal with uncertainty and structural complexity. Logical AI has focused mainly on handling com...
CORR
2008
Springer
14 years 9 months ago
2008
Springer
: Our research has shown that schedules can be built mimicking a human scheduler by using a set of rules that involve domain knowledge. This chapter presents a Bayesian Optimizatio...