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» Learning relational dependency networks in hybrid domains
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ML
2012
ACM
413views Machine Learning» more  ML 2012»
12 years 6 months ago
Gradient-based boosting for statistical relational learning: The relational dependency network case
Dependency networks approximate a joint probability distribution over multiple random variables as a product of conditional distributions. Relational Dependency Networks (RDNs) are...
Sriraam Natarajan, Tushar Khot, Kristian Kersting,...
CORR
2010
Springer
104views Education» more  CORR 2010»
13 years 11 months ago
Empirical learning aided by weak domain knowledge in the form of feature importance
Standard hybrid learners that use domain knowledge require stronger knowledge that is hard and expensive to acquire. However, weaker domain knowledge can benefit from prior knowle...
Ridwan Al Iqbal
KES
2007
Springer
14 years 4 months ago
A Hybrid Symbolic-Statistical Approach to Modeling Metabolic Networks
Biological systems consist of many components and interactions between them. In Systems Biology the principal problem is modeling complex biological systems and reconstructing inte...
Marenglen Biba, Stefano Ferilli, Nicola Di Mauro, ...
AAAI
2012
12 years 1 months ago
Learning Behavior Models for Hybrid Timed Systems
A tailored model of a system is the prerequisite for various analysis tasks, such as anomaly detection, fault identification, or quality assurance. This paper deals with the algo...
Oliver Niggemann, Benno Stein, Asmir Vodencarevic,...
CIDM
2009
IEEE
14 years 5 months ago
A new hybrid method for Bayesian network learning With dependency constraints
Abstract— A Bayes net has qualitative and quantitative aspects: The qualitative aspect is its graphical structure that corresponds to correlations among the variables in the Baye...
Oliver Schulte, Gustavo Frigo, Russell Greiner, We...