Theories for mutagenicity: a study in first-order and feature-based induction
Artificial Intelligence - Special volume on empirical methods
Boosting combinatorial search through randomization
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Resource-bounded Relational Reasoning: Induction and Deduction Through Stochastic Matching
Machine Learning - Special issue on multistrategy learning
Data Mining and Knowledge Discovery
Heavy-Tailed Phenomena in Satisfiability and Constraint Satisfaction Problems
Journal of Automated Reasoning
Phase Transitions in Relational Learning
Machine Learning
Carcinogenesis Predictions Using ILP
ILP '97 Proceedings of the 7th International Workshop on Inductive Logic Programming
Learning on the phase transition edge
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
Summarizing CSP hardness with continuous probability distributions
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
Randomised restarted search in ILP
Machine Learning
Improving inductive logic programming by using simulated annealing
Information Sciences: an International Journal
Boosting Descriptive ILP for Predictive Learning in Bioinformatics
Inductive Logic Programming
Parallel ILP for distributed-memory architectures
Machine Learning
Taming the Complexity of Inductive Logic Programming
SOFSEM '10 Proceedings of the 36th Conference on Current Trends in Theory and Practice of Computer Science
An empirical evaluation of bagging in inductive logic programming
ILP'02 Proceedings of the 12th international conference on Inductive logic programming
Using Bayesian networks to direct stochastic search in inductive logic programming
ILP'07 Proceedings of the 17th international conference on Inductive logic programming
Parameter Screening and Optimisation for ILP using Designed Experiments
The Journal of Machine Learning Research
April: an inductive logic programming system
JELIA'06 Proceedings of the 10th European conference on Logics in Artificial Intelligence
Strategies to parallelize ILP systems
ILP'05 Proceedings of the 15th international conference on Inductive Logic Programming
A study of applying dimensionality reduction to restrict the size of a hypothesis space
ILP'05 Proceedings of the 15th international conference on Inductive Logic Programming
Efficient sampling in relational feature spaces
ILP'05 Proceedings of the 15th international conference on Inductive Logic Programming
Learning theories using estimation distribution algorithms and (reduced) bottom clauses
ILP'11 Proceedings of the 21st international conference on Inductive Logic Programming
An approach to parallel class expression learning
RuleML'12 Proceedings of the 6th international conference on Rules on the Web: research and applications
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Recent empirical studies show that runtime distributions of backtrack procedures for solving hard combinatorial problems often have intriguing properties. Unlike standard distributions (such as the normal), such distributions decay slower than exponentially and have "heavy tails". Procedures characterized by heavy-tailed runtime distributions exhibit large variability in efficiency, but a very straightforward method called rapid randomized restarts has been designed to essentially improve their average performance. We show on two experimental domains that heavy-tailed phenomena can be observed in ILP, namely in the search for a clause in the subsumption lattice. We also reformulate the technique of randomized rapid restarts to make it applicable in ILP and show that it can reduce the average search-time.