Programming in Prolog (2nd ed.)
Programming in Prolog (2nd ed.)
Foundations of logic programming; (2nd extended ed.)
Foundations of logic programming; (2nd extended ed.)
POPL '87 Proceedings of the 14th ACM SIGACT-SIGPLAN symposium on Principles of programming languages
Quantifying inductive bias: AI learning algorithms and Valiant's learning framework
Artificial Intelligence
A decidable first-order logic for knowledge representation
Journal of Automated Reasoning
Towards a theory of access-limited logic for knowledge representation
Proceedings of the first international conference on Principles of knowledge representation and reasoning
The Utility of Knowledge in Inductive Learning
Machine Learning
Using constraints to building version spaces
ECML-94 Proceedings of the European conference on machine learning on Machine Learning
Flattening and Saturation: Two Representation Changes for Generalization
Machine Learning - Special issue on evaluating and changing representation
Artificial intelligence: a modern approach
Artificial intelligence: a modern approach
First-order jk-clausal theories are PAC-learnable
Artificial Intelligence
Approximate inference of functional dependencies from relations
ICDT '92 Selected papers of the fourth international conference on Database theory
Knowledge compilation and theory approximation
Journal of the ACM (JACM)
On the relative expressiveness of description logics and predicate logics
Artificial Intelligence
Theories for mutagenicity: a study in first-order and feature-based induction
Artificial Intelligence - Special volume on empirical methods
Solving the multiple instance problem with axis-parallel rectangles
Artificial Intelligence
Journal of the ACM (JACM)
Top-down induction of first-order logical decision trees
Artificial Intelligence
Algorithms for propositional KB approximation
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
A non-deterministic semantics for tractable inference
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Machine Learning
Inductive Logic Programming: Techniques and Applications
Inductive Logic Programming: Techniques and Applications
Learning Logical Definitions from Relations
Machine Learning
Theta-Subsumption for Structural Matching
ECML '97 Proceedings of the 9th European Conference on Machine Learning
FONN: Combining First Order Logic with Connectionist Learning
ICML '97 Proceedings of the Fourteenth International Conference on 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
Locally Finite, Proper and Complete Operators for Refining Datalog Programs
ISMIS '96 Proceedings of the 9th International Symposium on Foundations of Intelligent Systems
Part-of-Speech Tagging Using Progol
ILP '97 Proceedings of the 7th International Workshop on Inductive Logic Programming
NP-Completeness of the Set Unification and Matching Problems
Proceedings of the 8th International Conference on Automated Deduction
The predictive toxicology evaluation challenge
IJCAI'97 Proceedings of the 15th international joint conference on Artifical intelligence - Volume 1
Knowledge compilation using theory prime implicates
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Phase Transitions in Relational Learning
Machine Learning
Integrated Architectures for Machine Learning
Machine Learning and Its Applications, Advanced Lectures
Relational Learning Using Constrained Confidence-Rated Boosting
ILP '01 Proceedings of the 11th International Conference on Inductive Logic Programming
Theta-Subsumption in a Constraint Satisfaction Perspective
ILP '01 Proceedings of the 11th International Conference on Inductive Logic Programming
DS '01 Proceedings of the 4th International Conference on Discovery Science
Relational learning as search in a critical region
The Journal of Machine Learning Research
Scalability and efficiency in multi-relational data mining
ACM SIGKDD Explorations Newsletter
A Unifying Version-Space Representation
Annals of Mathematics and Artificial Intelligence
Fast Theta-Subsumption with Constraint Satisfaction Algorithms
Machine Learning
Answering constraint-based mining queries on itemsets using previous materialized results
Journal of Intelligent Information Systems
Learning Horn Expressions with LOGAN-H
The Journal of Machine Learning Research
QG/GA: a stochastic search for Progol
Machine Learning
QG/GA: A Stochastic Search for Progol
Inductive Logic Programming
Extension of the Top-Down Data-Driven Strategy to ILP
Inductive Logic Programming
Arc Consistency Projection: A New Generalization Relation for Graphs
ICCS '07 Proceedings of the 15th international conference on Conceptual Structures: Knowledge Architectures for Smart Applications
Concept Learning from (Very) Ambiguous Examples
MLDM '09 Proceedings of the 6th International Conference on Machine Learning and Data Mining in Pattern Recognition
Learning with feature description logics
ILP'02 Proceedings of the 12th 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
k-version-space multi-class classification based on k-consistency tests
ECML PKDD'10 Proceedings of the 2010 European conference on Machine learning and knowledge discovery in databases: Part III
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One of the obstacles to widely using first-order logiclanguages is the fact that relational inference is intractable in theworst case. Thispaper presents an any-time relational inferencealgorithm: it proceeds by stochastically sampling theinference search space, after this space has been judiciouslyrestricted using strongly-typed logic-like declarations.We present a relational learner producing programsgeared to stochastic inference, named STILL,to enforce the potentialities of this framework.STILL handles examples described as definite or constrained clauses,and uses sampling-based heuristics again to achieve any-time learning.Controlling both the construction and the exploitation of logic programsyields robust relational reasoning, where deductive biases arecompensated for by inductive biases, and vice versa.