Parameter Estimation in Stochastic Logic Programs
Machine Learning
New advances in logic-based probabilistic modeling by PRISM
Probabilistic inductive logic programming
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This project aims to investigate biologically inspired, logic-statistic models with constraints. The complexity and expressiveness of models with different kinds of constraints will be examined and algorithms to efficiently cope with inference in and training of such models will be explored. The models will be evaluated with regards to their applicability to biological sequence analysis.