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ILP
2007
Springer
14 years 1 months ago
Using Bayesian Networks to Direct Stochastic Search in Inductive Logic Programming
Stochastically searching the space of candidate clauses is an appealing way to scale up ILP to large datasets. We address an approach that uses a Bayesian network model to adaptive...
Louis Oliphant, Jude W. Shavlik
ECAI
2006
Springer
13 years 11 months ago
Smoothed Particle Filtering for Dynamic Bayesian Networks
Particle filtering (PF) for dynamic Bayesian networks (DBNs) with discrete-state spaces includes a resampling step which concentrates samples according to their relative weight in ...
Theodore Charitos
FEGC
2008
84views Biometrics» more  FEGC 2008»
13 years 9 months ago
Structure Inference of Bayesian Networks from Data: A New Approach Based on Generalized Conditional Entropy
We propose a novel algorithm for extracting the structure of a Bayesian network from a dataset. Our approach is based on generalized conditional entropies, a parametric family of e...
Dan A. Simovici, Saaid Baraty
JMLR
2006
169views more  JMLR 2006»
13 years 7 months ago
Bayesian Network Learning with Parameter Constraints
The task of learning models for many real-world problems requires incorporating domain knowledge into learning algorithms, to enable accurate learning from a realistic volume of t...
Radu Stefan Niculescu, Tom M. Mitchell, R. Bharat ...
UAI
1996
13 years 9 months ago
Efficient Approximations for the Marginal Likelihood of Incomplete Data Given a Bayesian Network
We discuss Bayesian methods for learning Bayesian networks when data sets are incomplete. In particular, we examine asymptotic approximations for the marginal likelihood of incomp...
David Maxwell Chickering, David Heckerman