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» Learning Stochastic Logic Programs
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ILP
2007
Springer
14 years 1 months ago
Learning with Kernels and Logical Representations
In this chapter, we describe a view of statistical learning in the inductive logic programming setting based on kernel methods. The relational representation of data and background...
Paolo Frasconi
GECCO
2003
Springer
156views Optimization» more  GECCO 2003»
14 years 27 days ago
Facts and Fallacies in Using Genetic Algorithms for Learning Clauses in First-Order Logic
Over the last few years, a few approaches have been proposed aiming to combine genetic and evolutionary computation (GECCO) with inductive logic programming (ILP). The underlying r...
Flaviu Adrian Marginean
ILP
2000
Springer
13 years 11 months ago
Learning First Order Logic Time Series Classifiers
A method for learning multivariate time series classifiers by inductive logic programming is presented. Two types of background predicate that are suited for this task are introduc...
Juan José Rodríguez, Carlos J. Alons...
BMCBI
2011
13 years 2 months ago
Using Stochastic Causal Trees to Augment Bayesian Networks for Modeling eQTL Datasets
Background: The combination of genotypic and genome-wide expression data arising from segregating populations offers an unprecedented opportunity to model and dissect complex phen...
Kyle C. Chipman, Ambuj K. Singh
IJCAI
2001
13 years 9 months ago
Symbolic Dynamic Programming for First-Order MDPs
We present a dynamic programming approach for the solution of first-order Markov decisions processes. This technique uses an MDP whose dynamics is represented in a variant of the ...
Craig Boutilier, Raymond Reiter, Bob Price