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» Probabilistic Inductive Logic Programming
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JIIS
2008
89views more  JIIS 2008»
13 years 8 months ago
A note on phase transitions and computational pitfalls of learning from sequences
An ever greater range of applications call for learning from sequences. Grammar induction is one prominent tool for sequence learning, it is therefore important to know its proper...
Antoine Cornuéjols, Michèle Sebag
IDT
2010
124views more  IDT 2010»
13 years 7 months ago
Modelling decision making with probabilistic causation
Humans know how to reason based on cause and effect, but cause and effect is not enough to draw conclusions due to the problem of imperfect information and uncertainty. To resol...
Luís Moniz Pereira, Carroline Kencana Ramli
ILP
2005
Springer
14 years 2 months ago
Strategies to Parallelize ILP Systems
Abstract. It is well known by Inductive Logic Programming (ILP) practioners that ILP systems usually take a long time to find valuable models (theories). The problem is specially ...
Nuno A. Fonseca, Fernando M. A. Silva, Rui Camacho
AIMSA
2000
Springer
14 years 1 months ago
Least Generalization under Relative Implication
Inductive Logic Programming (ILP) deals with inducing clausal theories from examples basically through generalization or specialization. The specialization and generalization oper...
Svetla Boytcheva
PKDD
2000
Springer
120views Data Mining» more  PKDD 2000»
14 years 10 days ago
Multi-Relational Data Mining, Using UML for ILP
Although there is a growing need for multi-relational data mining solutions in KDD, the use of obvious candidates from the field of Inductive Logic Programming (ILP) has been limit...
Arno J. Knobbe, Arno Siebes, Hendrik Blockeel, Dan...