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» Dynamic Modeling in Inductive Inference
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ICLP
2010
Springer
13 years 11 months ago
Improving the Efficiency of Gibbs Sampling for Probabilistic Logical Models by Means of Program Specialization
Abstract. There is currently a large interest in probabilistic logical models. A popular algorithm for approximate probabilistic inference with such models is Gibbs sampling. From ...
Daan Fierens
ICML
2007
IEEE
14 years 8 months ago
A permutation-augmented sampler for DP mixture models
We introduce a new inference algorithm for Dirichlet process mixture models. While Gibbs sampling and variational methods focus on local moves, the new algorithm makes more global...
Percy Liang, Michael I. Jordan, Benjamin Taskar
IFIP
2007
Springer
14 years 2 months ago
Semantic Context Reasoning Using Ontology Based Models
New mobile computing technologies and the increasing use of portable devices have pushed the development of the so-called context-aware applications. This new class of applications...
Rodrigo Mantovaneli Pessoa, Camilo Zardo Calvi, Jo...
ISSTA
2009
ACM
14 years 2 months ago
Precise pointer reasoning for dynamic test generation
Dynamic test generation consists of executing a program while gathering symbolic constraints on inputs from predicates encountered in branch statements, and of using a constraint ...
Bassem Elkarablieh, Patrice Godefroid, Michael Y. ...
ICML
2010
IEEE
13 years 9 months ago
Probabilistic Backward and Forward Reasoning in Stochastic Relational Worlds
Inference in graphical models has emerged as a promising technique for planning. A recent approach to decision-theoretic planning in relational domains uses forward inference in d...
Tobias Lang, Marc Toussaint