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» Learning Probabilistic Models of Relational Structure
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ML
2006
ACM
122views Machine Learning» more  ML 2006»
13 years 5 months ago
PRL: A probabilistic relational language
In this paper, we describe the syntax and semantics for a probabilistic relational language (PRL). PRL is a recasting of recent work in Probabilistic Relational Models (PRMs) into ...
Lise Getoor, John Grant
ECML
2007
Springer
13 years 11 months ago
Learning Directed Probabilistic Logical Models: Ordering-Search Versus Structure-Search
We discuss how to learn non-recursive directed probabilistic logical models from relational data. This problem has been tackled before by upgrading the structure-search algorithm i...
Daan Fierens, Jan Ramon, Maurice Bruynooghe, Hendr...
ICML
2009
IEEE
14 years 6 months ago
Approximate inference for planning in stochastic relational worlds
Relational world models that can be learned from experience in stochastic domains have received significant attention recently. However, efficient planning using these models rema...
Tobias Lang, Marc Toussaint
VLDB
2008
ACM
196views Database» more  VLDB 2008»
14 years 5 months ago
Modelling retrieval models in a probabilistic relational algebra with a new operator: the relational Bayes
This paper presents a probabilistic relational modelling (implementation) of the major probabilistic retrieval models. Such a high-level implementation is useful since it supports ...
Thomas Rölleke, Hengzhi Wu, Jun Wang, Hany Azzam
JAIR
2010
145views more  JAIR 2010»
13 years 3 months ago
Planning with Noisy Probabilistic Relational Rules
Noisy probabilistic relational rules are a promising world model representation for several reasons. They are compact and generalize over world instantiations. They are usually in...
Tobias Lang, Marc Toussaint