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» On Using Machine Learning for Logic BIST
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ICML
1989
IEEE
13 years 11 months ago
Higher-Order and Modal Logic as a Framework for Explanation-Based Generalization
Logic programming provides a uniform framework in which all aspects of explanation-based generalization and learning may be defined and carried out, but first-order Horn logic i...
Scott Dietzen, Frank Pfenning
ML
2008
ACM
100views Machine Learning» more  ML 2008»
13 years 7 months ago
Generalized ordering-search for learning directed probabilistic logical models
Abstract. Recently, there has been an increasing interest in directed probabilistic logical models and a variety of languages for describing such models has been proposed. Although...
Jan Ramon, Tom Croonenborghs, Daan Fierens, Hendri...
AIIA
2005
Springer
14 years 1 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...
AAAI
1993
13 years 8 months ago
Learning Semantic Grammars with Constructive Inductive Logic Programming
Automating the construction of semantic grammars is a di cult and interesting problem for machine learning. This paper shows how the semantic-grammar acquisition problem can be vi...
John M. Zelle, Raymond J. Mooney
ML
1998
ACM
115views Machine Learning» more  ML 1998»
13 years 7 months ago
Pharmacophore Discovery Using the Inductive Logic Programming System PROGOL
This paper is a case study of a machine aided knowledge discovery process within the general area of drug design. More speci cally, the paper describes a sequence of experiments in...
Paul W. Finn, Stephen Muggleton, David Page, Ashwi...