Graph-Based Algorithms for Boolean Function Manipulation
IEEE Transactions on Computers
Relational learning with statistical predicate invention: better models for hypertext
Machine Learning - Special issue on inducive logic programming
Parameter Estimation in Stochastic Logic Programs
Machine Learning
Machine Learning
Logical and Relational Learning: From ILP to MRDM (Cognitive Technologies)
Logical and Relational Learning: From ILP to MRDM (Cognitive Technologies)
Introduction to Statistical Relational Learning (Adaptive Computation and Machine Learning)
Introduction to Statistical Relational Learning (Adaptive Computation and Machine Learning)
Parameter Learning in Probabilistic Databases: A Least Squares Approach
ECML PKDD '08 Proceedings of the 2008 European Conference on Machine Learning and Knowledge Discovery in Databases - Part I
A Simple Model for Sequences of Relational State Descriptions
ECML PKDD '08 Proceedings of the European conference on Machine Learning and Knowledge Discovery in Databases - Part II
Learning Ground CP-Logic Theories by Leveraging Bayesian Network Learning Techniques
Fundamenta Informaticae - Progress on Multi-Relational Data Mining
Parameter learning of logic programs for symbolic-statistical modeling
Journal of Artificial Intelligence Research
ProbLog: a probabilistic prolog and its application in link discovery
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Probabilistic inductive logic programming: theory and applications
Probabilistic inductive logic programming: theory and applications
The independent choice logic and beyond
Probabilistic inductive logic programming
Markov Logic: An Interface Layer for Artificial Intelligence
Markov Logic: An Interface Layer for Artificial Intelligence
Representing causal information about a probabilistic process
JELIA'06 Proceedings of the 10th European conference on Logics in Artificial Intelligence
Learning the structure of probabilistic logic programs
ILP'11 Proceedings of the 21st international conference on Inductive Logic Programming
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
MCINTYRE: A Monte Carlo System for Probabilistic Logic Programming
Fundamenta Informaticae - Special Issue on the Italian Conference on Computational Logic: CILC 2011
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ProbLog is a recently introduced probabilistic extension of the logic programming language Prolog, in which facts can be annotated with the probability that they hold. The advantage of this probabilistic language is that it naturally expresses a generative process over interpretations using a declarative model. Interpretations are relational descriptions or possible worlds. This paper introduces a novel parameter estimation algorithm LFI-ProbLog for learning ProbLog programs from partial interpretations. The algorithm is essentially a Soft-EM algorithm. It constructs a propositional logic formula for each interpretation that is used to estimate the marginals of the probabilistic parameters. The LFI-ProbLog algorithm has been experimentally evaluated on a number of data sets that justifies the approach and shows its effectiveness