New Generation Computing - Selected papers from the international workshop on algorithmic learning theory,1990
An entropy-based learning algorithm of Bayesian conditional trees
UAI '92 Proceedings of the eighth conference on Uncertainty in Artificial Intelligence
Machine Learning - Special issue on learning with probabilistic representations
Parameter Estimation in Stochastic Logic Programs
Machine Learning
Database Management Systems
Learning Probabilistic Relational Models
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
ILP '96 Selected Papers from the 6th International Workshop on Inductive Logic Programming
Statistical Relational Learning for Document Mining
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
Aggregation-based feature invention and relational concept classes
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Learning relational probability trees
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Learning bayesian network structure from massive datasets: the «sparse candidate« algorithm
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
CLP(BN): constraint logic programming for probabilistic knowledge
UAI'03 Proceedings of the Nineteenth conference on Uncertainty in Artificial Intelligence
Learning Bayesian networks of rules with SAYU
MRDM '05 Proceedings of the 4th international workshop on Multi-relational mining
The relationship between Precision-Recall and ROC curves
ICML '06 Proceedings of the 23rd international conference on Machine learning
Change of representation for statistical relational learning
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
CLP(BN): constraint logic programming for probabilistic knowledge
Probabilistic inductive logic programming
An inductive logic programming approach to validate Hexose binding biochemical knowledge
ILP'09 Proceedings of the 19th international conference on Inductive logic programming
Constrained sequential pattern knowledge in multi-relational learning
EPIA'11 Proceedings of the 15th Portugese conference on Progress in artificial intelligence
An integrated approach to learning bayesian networks of rules
ECML'05 Proceedings of the 16th European conference on Machine Learning
Prolog performance on larger datasets
PADL'07 Proceedings of the 9th international conference on Practical Aspects of Declarative Languages
Predictive sequence miner in ILP learning
ILP'11 Proceedings of the 21st international conference on Inductive Logic Programming
Relational differential prediction
ECML PKDD'12 Proceedings of the 2012 European conference on Machine Learning and Knowledge Discovery in Databases - Volume Part I
Reducing the size of databases for multirelational classification: a subgraph-based approach
Journal of Intelligent Information Systems
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Statistical relational learning (SRL) constructs probabilistic models from relational databases. A key capability of SRL is the learning of arcs (in the Bayes net sense) connecting entries in different rows of a relational table, or in different tables. Nevertheless, SRL approaches currently are constrained to use the existing database schema. For many database applications, users find it profitable to define alternative "views" of the database, in effect defining new fields or tables. Such new fields or tables can also be highly useful in learning. We provide SRL with the capability of learning new views.