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Abstract: Probabilistic inductive logic programming, sometimes also called statistical relational learning, addresses one of the central questions of artificial intelligence: the integration of probabilistic reasoning with first order logic representations and machine learning. A rich variety of di#erent formalisms and learning techniques have been developed. In the present paper, we start from inductive logic programming and sketch how it can be extended with probabilistic methods. (Update)
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BibTeX entry: (Update)
L. De Raedt and K. Kersting. Probabilistic Inductive Logic Programming. In Proceedings of the 15th International Conference on Algorithmic Learning Theory (ALT-2004. http://citeseer.ist.psu.edu/article/deraedt04probabilistic.html More
@misc{ raedt04probabilistic,
author = "L. De Raedt and K. Kersting",
title = "Probabilistic Inductive Logic Programming",
text = "L. De Raedt and K. Kersting. Probabilistic Inductive Logic Programming.
In Proceedings of the 15th International Conference on Algorithmic Learning
Theory (ALT-2004.",
year = "2004",
url = "citeseer.ist.psu.edu/article/deraedt04probabilistic.html" }
Citations (may not include all citations):2528 Maximum likelihood from incomplete data via the EM algorithm (context) - Dempster, Laird et al. - 1977
493 Communications of the ACM (context) - Valiant, of et al. - 1984
475 Building a large annotated corpus of English: The Penn TREEB.. - Marcus, Marcinkiewicz et al. - 1993
328 Foundations of Statistical Natural Language Processing - Manning, Schutze - 1999
328 Algorithmic Program Debugging (context) - Shapiro - 1983
267 A note on inductive generalization (context) - Plotkin - 1970
226 The EM Algorithm and Extensions (context) - McKachlan, Krishnan - 1997
219 A Tutorial on Learning with Bayesian Networks - Heckerman - 1995
138 Probabilistic Horn abduction and Bayesian networks - Poole - 1993
130 Inverse Entailment and Progol - Muggleton - 1995
85 Theories for mutagenicity: A study of first-order and featur.. - Srinivasan, Muggleton et al. - 1996
53 Stochastic logic programs - Muggleton - 1996
48 Inducing Probabilistic Grammars by Bayesian Model Merging - Stolcke, Omohundro - 1994
46 Probabilistic frame-based systems - Koller, Pfe - 1998
41 Stochastic Attribute-Value Grammars - Abney - 1997
38 Clausal discovery - De Raedt, Dehaspe - 1997
37 The McGraw-Hill Companies (context) - Mitchell - 1997
34 Foundations of Inductive Logic Programming (context) - Nienhuys-Cheng, de Wolf - 1997
32 Inductive Logic Programming: From Machine Learning to Softwa.. (context) - Bergadano, Gunetti - 1996
30 Induction as nonmonotonic inference (context) - Helft - 1989
29 Induction of logic programs: FOIL and related systems - Quinlan, Cameron-Jones - 1995
28 Answering queries from context-sensitive probabilistic knowl.. - Ngo, Haddawy - 1997
27 Logical settings for concept-learning (context) - De Raedt - 1997
25 First-Order jk-Clausal Theories are PAC-Learnable (context) - De Raedt, Dzeroski - 1994
24 Relational Bayesian networks - Jaeger - 1997
21 Relational Markov Models and their Application to Adaptive W.. - Anderson, Domingos et al. - 2002
19 cient induction of logic programs (context) - Muggleton, Feng - 1992
15 A Statistical Learning Method for Logic Programs with Distri.. - Sato - 1995
13 Parameter estimation in stochastic logic programs - Cussens - 2001
12 Towards discovering structural signatures of protein folds b.. - Kersting, Raiko et al. - 2003
12 Reasoning in Intelligent Systems: Networks of Plausible Infe.. (context) - Pearl - 1991
11 Artificial Intelligence Review (context) - Furnkranz, Learning - 1999
10 Loglinear models for first-order probabilistic reasoning - Cussens - 1999
10 Institute for Computer Science (context) - Kersting, De Raedt et al. - 2001
10 Towards Combining Inductive Logic Programming and Bayesian N.. - Kersting, De Raedt - 2001
5 Probabilistic Reasoning for Complex Systems (context) - Pfe - 2000
4 Adaptive Bayesian Logic Programs - Kersting, De Raedt - 2001
3 Generating Bayesian networks from probabilistic logic knowle.. (context) - Haddawy - 1994
2 Electronic Transactions in Artificial Intelligence (context) - Muggleton, logic - 2000
2 Springer-Verlag New (context) - Jensen, decision - 2001
2 Learning structure and parameters of stochastic logic progra.. (context) - Muggleton - 2002
2 Principles of Learning Bayesian Logic Programs (context) - Kersting, De Raedt - 2002
2 ACM-SIGKDD Explorations: Special issue on Multi-Relational D.. (context) - De Raedt, Kersting et al. - 2003
2 Towards probabilistic extensions of contraint-based grammars (context) - Eisele - 1994
1 Workshop on Learning Statistical Models from Relational Data (context) - Getoor, Jensen et al. - 2003
1 Workshop on Statistical Relational Learning and its Connecti.. (context) - Dietterich, Getoor et al. - 2004
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