22 search results - page 3 / 5 » Using Bayesian Networks to Direct Stochastic Search in Induc... |
ECML
2005
Springer
14 years 1 months ago
2005
Springer
Abstract. Learning from multi-relational domains has gained increasing attention over the past few years. Inductive logic programming (ILP) systems, which often rely on hill-climbi...
AI
2000
Springer
13 years 7 months ago
2000
Springer
Markov decisionprocesses(MDPs) haveproven to be popular models for decision-theoretic planning, but standard dynamic programming algorithms for solving MDPs rely on explicit, stat...
ICML
2005
IEEE
14 years 8 months ago
2005
IEEE
Markov logic networks (MLNs) combine logic and probability by attaching weights to first-order clauses, and viewing these as templates for features of Markov networks. In this pap...
ILP
2007
Springer
14 years 1 months ago
2007
Springer
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...
CORR
2011
Springer
12 years 11 months ago
2011
Springer
We propose a logical/mathematical framework for statistical parameter learning of parameterized logic programs, i.e. de nite clause programs containing probabilistic facts with a ...