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» Probabilistic Inductive Logic Programming
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AIIA
2005
Springer
14 years 2 months ago
Handling Continuous-Valued Attributes in Incremental First-Order Rules Learning
Machine Learning systems are often distinguished according to the kind of representation they use, which can be either propositional or first-order logic. The framework working wi...
Teresa Maria Altomare Basile, Floriana Esposito, N...
ILP
2003
Springer
14 years 2 months ago
Hybrid Abductive Inductive Learning: A Generalisation of Progol
The learning system Progol5 and the underlying inference method of Bottom Generalisation are firmly established within Inductive Logic Programming (ILP). But despite their success...
Oliver Ray, Krysia Broda, Alessandra Russo
JMLR
2006
112views more  JMLR 2006»
13 years 8 months ago
Kernels on Prolog Proof Trees: Statistical Learning in the ILP Setting
We develop kernels for measuring the similarity between relational instances using background knowledge expressed in first-order logic. The method allows us to bridge the gap betw...
Andrea Passerini, Paolo Frasconi, Luc De Raedt
IANDC
2006
117views more  IANDC 2006»
13 years 8 months ago
A modular approach to defining and characterising notions of simulation
We propose a modular approach to defining notions of simulation, and modal logics which characterise them. We use coalgebras to model state-based systems, relators to define notio...
Corina Cîrstea
IJCAI
2007
13 years 10 months ago
ProbLog: A Probabilistic Prolog and Its Application in Link Discovery
We introduce ProbLog, a probabilistic extension of Prolog. A ProbLog program defines a distribution over logic programs by specifying for each clause the probability that it belo...
Luc De Raedt, Angelika Kimmig, Hannu Toivonen