Foundations of logic programming; (2nd extended ed.)
Foundations of logic programming; (2nd extended ed.)
Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic Horn abduction and Bayesian networks
Artificial Intelligence
Answering queries from context-sensitive probabilistic knowledge bases
Selected papers from the international workshop on Uncertainty in databases and deductive systems
Adaptive Probabilistic Networks with Hidden Variables
Machine Learning - Special issue on learning with probabilistic representations
Advances in Inductive Logic Programming
Advances in Inductive Logic Programming
Parameter Estimation in Stochastic Logic Programs
Machine Learning
Probabilistic Networks and Expert Systems
Probabilistic Networks and Expert Systems
Probabilistic Relational Models
ILP '99 Proceedings of the 9th International Workshop on Inductive Logic Programming
Towards Combining Inductive Logic Programming with Bayesian Networks
ILP '01 Proceedings of the 11th International Conference on Inductive Logic Programming
Bayesian Logic Programs
Learning probabilities for noisy first-order rules
IJCAI'97 Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2
Learning probabilistic relational models
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
UAI'97 Proceedings of the Thirteenth conference on Uncertainty in artificial intelligence
First-Order Probabilistic Languages: Into the Unknown
Inductive Logic Programming
A Statistical Approach to Incremental Induction of First-Order Hierarchical Knowledge Bases
ILP '08 Proceedings of the 18th international conference on Inductive Logic Programming
On the Relationship between Hybrid Probabilistic Logic Programs and Stochastic Satisfiability
SUM '08 Proceedings of the 2nd international conference on Scalable Uncertainty Management
A Logical Approach to Qualitative and Quantitative Reasoning
ECSQARU '07 Proceedings of the 9th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
Approaches to Uncertain or Imprecise Rules - A Survey
RuleML '09 Proceedings of the 2009 International Symposium on Rule Interchange and Applications
Discriminative Markov logic network structure learning based on propositionalization and X2-test
ADMA'10 Proceedings of the 6th international conference on Advanced data mining and applications: Part I
Incomplete knowledge in hybrid probabilistic logic programs
JELIA'06 Proceedings of the 10th European conference on Logics in Artificial Intelligence
Fisher kernels for relational data
ECML'06 Proceedings of the 17th European conference on Machine Learning
CLP(BN): constraint logic programming for probabilistic knowledge
UAI'03 Proceedings of the Nineteenth conference on Uncertainty in Artificial Intelligence
Statistical relational learning: an inductive logic programming perspective
PKDD'05 Proceedings of the 9th European conference on Principles and Practice of Knowledge Discovery in Databases
Statistical relational learning: an inductive logic programming perspective
ECML'05 Proceedings of the 16th European conference on Machine Learning
Intelligent environments for next-generation e-markets
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part I
Logical bayesian networks and their relation to other probabilistic logical models
ILP'05 Proceedings of the 15th international conference on Inductive Logic Programming
Towards a more practical hybrid probabilistic logic programming framework
PADL'05 Proceedings of the 7th international conference on Practical Aspects of Declarative Languages
Lifted online training of relational models with stochastic gradient methods
ECML PKDD'12 Proceedings of the 2012 European conference on Machine Learning and Knowledge Discovery in Databases - Volume Part I
Inference in probabilistic logic programs with continuous random variables
Theory and Practice of Logic Programming
Model checking with probabilistic tabled logic programming
Theory and Practice of Logic Programming
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First order probabilistic logics combine a first order logic with a probabilistic knowledge representation. In this context, we introduce continuous Bayesian logic programs, which extend the recently introduced Bayesian logic programs to deal with continuous random variables. Bayesian logic programs tightly integrate definite logic programs with Bayesian networks. The resulting framework nicely seperates the qualitative (i.e. logical) component from the quantitative (i.e. the probabilistic) one. We also show how the quantitative component can be learned using a gradient-based maximum likelihood method.