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» Fixed-Parameter Complexity of Semantics for Logic Programs
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CORR
2011
Springer
174views Education» more  CORR 2011»
14 years 1 months ago
Parameter Learning of Logic Programs for Symbolic-Statistical Modeling
We propose a logical/mathematical framework for statistical parameter learning of parameterized logic programs, i.e. de nite clause programs containing probabilistic facts with a ...
Yoshitaka Kameya, Taisuke Sato
AAAI
2004
14 years 11 months ago
Logic Programs with Abstract Constraint Atoms
We propose and study extensions of logic programming with constraints represented as generalized atoms of the form C(X), where X is a finite set of atoms and C is act constraint (...
Victor W. Marek, Miroslaw Truszczynski
CORR
2010
Springer
180views Education» more  CORR 2010»
14 years 6 months ago
XSB: Extending Prolog with Tabled Logic Programming
The paradigm of Tabled Logic Programming (TLP) is now supported by a number of Prolog systems, including XSB, YAP Prolog, B-Prolog, Mercury, ALS, and Ciao. The reasons for this ar...
Terrance Swift, David Scott Warren
ICDAR
2009
IEEE
15 years 4 months ago
Inductive Logic Programming for Symbol Recognition
In this paper, we make an attempt to use Inductive Logic Programming (ILP) to automatically learn non trivial descriptions of symbols, based on a formal description. This work is ...
K. C. Santosh, Bart Lamiroy, Jean-Philippe Ropers
ML
2006
ACM
122views Machine Learning» more  ML 2006»
14 years 9 months ago
PRL: A probabilistic relational language
In this paper, we describe the syntax and semantics for a probabilistic relational language (PRL). PRL is a recasting of recent work in Probabilistic Relational Models (PRMs) into ...
Lise Getoor, John Grant