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Luc De Raedt, Kristian Kersting



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Abstract: The past few years have witnessed an significant interest in probabilistic logic learning, i.e. in research lying at the intersection of probabilistic reasoning, logical representations, and machine learning. A rich variety of di#erent formalisms and learning techniques have been developed. This paper provides an introductory survey and overview of the stateof -the-art in probabilistic logic learning through the identification of a number of important probabilistic, logical and learning... (Update)

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1.2:   Basic Principles of Learning Bayesian Logic Programs - Kersting, De Raedt (2002)   (Correct)

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BibTeX entry:   (Update)

L. De Raedt and K. Kersting. Probabilistic logic learning. ACM-SIGKDD Explor., 5, 2004. http://citeseer.ist.psu.edu/deraedt04probabilistic.html   More

@misc{ raedt04probabilistic,
  author = "L. De Raedt and K. Kersting",
  title = "Probabilistic logic learning",
  text = "L. De Raedt and K. Kersting. Probabilistic logic learning. ACM-SIGKDD Explor.,
    5, 2004.",
  year = "2004",
  url = "citeseer.ist.psu.edu/deraedt04probabilistic.html" }
Citations (may not include all citations):
2528   Maximum likelihood from incomplete data via the EM algorithm (context) - Dempster, Laird et al. - 1977
1838   Foundations of Logic Programming (context) - Lloyd - 1989
1749   An Introduction to Probability Theory and its Applications: .. (context) - Feller - 1968
1362   A Tutorial on Hidden Markov Models and Selected Applications.. (context) - Rabiner - 1989
410   Principles of Artificial Intelligence (context) - Nilsson - 1986
362   An introduction to hidden Markov models (context) - Rabiner, Juang - 1986
328   Foundations of Statistical Natural Language Processing - Manning, Schutze - 1999
328   Algorithmic Program Debugging (context) - Shapiro - 1983
313   Inductive logic programming: Theory and methods - Muggleton, De Raedt - 1994
250   Artificial Intelligence: A Modern Approach (context) - Russell, Norvig - 1995
226   The EM Algorithm and Extensions (context) - McKachlan, Krishnan - 1997
219   A Tutorial on Learning with Bayesian Networks - Heckerman - 1995
144   Probabilistic networks and expert systems (context) - Cowell, Dawid et al. - 1999
138   Probabilistic Horn abduction and Bayesian networks - Poole - 1993
137   An analysis of first--order logics of probability - Halpern - 1989
136   Biological Sequence Analysis: Probabilistic models of protei.. (context) - Durbin, Eddy et al. - 1998
103   Learning probabilistic relational models - Friedman, Getoor et al. - 1999
103   Learning probabilistic relational models - Getoor, Friedman et al. - 2001
79   Probabilistic Logic Programming - Ng, Subrahmanian - 1992
74   The Bayesian Structural EM Algorithm - Friedman - 1998
74   A guide to the literature on learning probabilistic networks.. - Buntine - 1996
59   Object-oriented Bayesian networks - Koller, Pfe - 1997
56   Gradient-Based Learning Algorithms for Recurrent Networks an.. - Williams, Zipser - 1995
55   A general framework for adaptive processing of data structur.. - Frasconi, Gori et al. - 1998
53   Probabilistic temporal reasoning (context) - Dean, Kanazawa - 1988
53   Stochastic logic programs - Muggleton - 1996
46   Probabilistic frame-based systems - Koller, Pfe - 1998
44   Construction of Belief and decision networks (context) - Breese - 1992
38   Clausal discovery - De Raedt, Dehaspe - 1997
37   Logic Programs with Uncertainties: A Tool for Implementing E.. (context) - Shapiro - 1983
34   Foundations of Inductive Logic Programming (context) - Nienhuys-Cheng, de Wolf - 1997
33   Relational Data Mining (context) - Dzeroski, Lavrac - 2001
32   Inductive Logic Programming: From Machine Learning to Softwa.. (context) - Bergadano, Gunetti - 1996
28   Answering queries from context--sensitive probabilistic know.. - Ngo, Haddawy - 1997
28   BC: A first-order Bayesian classifier - Flach, Lachiche - 1999
27   Logical settings for concept-learning (context) - De Raedt - 1997
24   Relational Bayesian networks - Jaeger - 1997
23   Interactive Theory Revision: An Inductive Logic Programming .. (context) - De Raedt - 1992
21   Dynamic construction of belief networks (context) - Goldman, Charniak - 1990
21   Relational Markov Models and their Application to Adaptive W.. - Anderson, Domingos et al. - 2002
21   Relational Learning with Statistical Predicate Invention: Be.. - Craven, Slattery - 2001
20   classic: A tractable probabilistic description logic (context) - Koller, Levy et al. - 1997
18   Tree induction for probability-based ranking - Provost, Domingos - 2003
18   Rich Probabilistic Models for Gene Expression - Segal, Taskar et al. - 2001
18   Identity Uncertainty and Citation Matching - Pasula, Marthi et al. - 2003
16   Learning Probabilistic Models of Relational Structure - Getoor, Friedman et al. - 2001
16   Simply logical: intelligent reasoning by example (context) - Flach - 1994
15   A Statistical Learning Method for Logic Programs with Distri.. - Sato - 1995
15   Probabilistic relational models (context) - Koller - 1999
13   Parameter estimation in stochastic logic programs - Cussens - 2001
12   Learning probabilities for noisy first-order rules - Koller, Pfe - 1997
12   Constructing Flexible Dynamic Belief Networks from First-Ord.. - Glesner, Koller - 1995
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
12   Linkage and autocorrelation cause feature selection bias in .. - Jensen, Neville - 2002
11   Probabilistic Models of Text and Link Structure for Hypertex.. - Getoor, Segal et al. - 2001
11   Kluwer Academic Publishers (context) - Jordan, in et al. - 1998
11   Using first-order probability logic for the construction of .. - Bacchus - 1993
10   Towards Combining Inductive Logic Programming and Bayesian N.. - Kersting, De Raedt - 2001
10   Loglinear models for first-order probabilistic reasoning - Cussens - 1999
10   Institute for Computer Science (context) - Kersting, De Raedt et al. - 2001
10   Approximate inference for first-order probabilistic language.. - Pasula, Russell - 2001
8   Parameter learning of logic programs for symbolic-statistica.. - Sato, Kameya - 2001
7   Clinical Simulation using Context-Sensitive Temporal Probabi.. - Haddawy, Helwig et al. - 1995
7   From Promoter Sequence to Expression: A Probabilistic Framew.. - Segal, Barash et al. - 2002
7   Probabilistic clustering in relational data (context) - Taskar, Segal et al. - 2001
7   Learning stochastic logic programs - Muggleton - 2000
6   BC2: A True First-Order Bayesian Classifier - Lachiche, Flach - 2002
6   First Order Theory Refinement - Wrobel - 1996
5   Stochastic logic programs: Sampling (context) - Cussens - 2000
5   Statistical Models for Relational Data (context) - Getoor, Koller et al. - 2002
5   Probabilistic Reasoning for Complex Systems (context) - Pfe - 2000
5   PRISM: A Symbolic-- Statistical Modeling Language (context) - Sato, Kameya - 1997
4   A Viterbi-like algorithm and EM learning for statistical abd.. - Sato, Kameya - 2000
4   Markov chain Monte Carlo using tree-based priors on model st.. (context) - Angelopoulos, Cussens - 2001
4   Adaptive Bayesian Logic Programs - Kersting, De Raedt - 2001
4   Spook: A system for probabilistic object-oriented knowledge .. (context) - Pfe, Koller et al. - 1999
3   Constraint Logic Programming for Probabilistic Knowledge (context) - Costa, Page et al. - 2003
3   Semantics and Inference for Recursive Probability Models (context) - Pfe, Koller - 2000
3   Decomposing Gene Expression into Cellular Processes - Segal, Battle et al. - 2003
3   A graphical method for parameter learning of symbolic-statis.. - Kameya, Ueda et al. - 1999
3   Hidden Tree Markov Models for Document Image Classification - Diligenti, Frasconi et al. - 2003
3   Generating Bayesian networks from probabilistic logic knowle.. (context) - Haddawy - 1994
3   Learning probabilistic relational models with structural unc.. - Getoor, Koller et al. - 2000
2   Introduction to the special section on knowledge-based const.. (context) - Breese, Goldman et al. - 1994
2   PROLOG: A Language for Implementing Expert Systems (context) - Clark, McCabe - 1982
2   Towards probabilistic extensions of contraint-based grammars (context) - Eisele - 1994
2   Springer-Verlag New (context) - Jensen, decision - 2001
2   Electronic Transactions in Artificial Intelligence (context) - Muggleton, logic - 2000
2   Learning structure and parameters of stochastic logic progra.. (context) - Muggleton - 2002
2   Learning Statistical Models from Relational Data (context) - Getoor - 2001
2   A Knowledge-Based Model Construction Approach to Medical Dec.. - Ngo, Haddawy - 1996
2   cient EM learning with tabulation for parameterized logic pr.. (context) - Kameya, Sato - 2000
2   Principles of Learning Bayesian Logic Programs (context) - Kersting, De Raedt - 2002
1   Learning Structured Statistical Models from Relational Data (context) - Getoor, Friedman et al. - 2002
1   A Structural GEM for Learning Logical Hidden Markov Models (context) - Kersting, Raiko et al. - 2003
1   Benjamin /Cummings Series in Computer Science (context) - Allen, Understanding - 1987
1   Statistical aspects of stochastic logic programs (context) - Cussens - 2001
1   Parameterized logic programs where computing meets learning - Sato - 2024
1   Selectivity Estimation using Probabilistic Relational Models (context) - Getoor, Taskar et al. - 2001

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