Algorithmics: theory & practice
Algorithmics: theory & practice
Exploiting the deep structure of constraint problems
Artificial Intelligence
Machine Learning
Phase Transitions in Relational Learning
Machine Learning
Learning Logical Definitions from Relations
Machine Learning
An Experimental Evaluation of Coevolutive Concept Learning
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
An Experimental Study of Phase Transitions in Matching
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
Scalability and efficiency in multi-relational data mining
ACM SIGKDD Explorations Newsletter
A Model to Study Phase Transition and Plateaus in Relational Learning
ILP '08 Proceedings of the 18th international conference on Inductive Logic Programming
Lattice-search runtime distributions may be heavy-tailed
ILP'02 Proceedings of the 12th international conference on Inductive logic programming
Learning discriminant rules as a minimal saturation search
ILP'10 Proceedings of the 20th international conference on Inductive logic programming
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Extracting rules from RBFs is not a trivial task because of nonlinear functions or high input dimensionality. In such cases, some of the hidden units of the RBF network have a tendency to be "shared" across several output classes or even may not contribute ...