Statistical Relational Learning: An Inductive Logic Programming Perspective

Author:

De Raedt Luc

Publisher

Springer Berlin Heidelberg

Reference19 articles.

1. Anderson, C.R., Domingos, P., Weld, D.S.: Relational Markov Models and their Application to Adaptive Web Navigation. In: Hand, D., Keim, D., Zaïne, O.R., Goebel, R. (eds.) Proceedings of the Eighth International Conference on Knowledge Discovery and Data Mining (KDD 2002), Edmonton, Canada, pp. 143–152. ACM Press, New York (2002)

2. Cussens, J.: Loglinear models for first-order probabilistic reasoning. In: Laskey, K.B., Prade, H. (eds.) Proceedings of the Fifteenth Annual Conference on Uncertainty in Artificial Intelligence (UAI 1999), Stockholm, Sweden, pp. 126–133. Morgan Kaufmann, San Francisco (1999)

3. De Raedt, L.: Logical settings for concept-learning. Artificial Intelligence 95(1), 197–201 (1997)

4. De Raedt, L., Kersting, K.: Probabilistic Logic Learning. ACM-SIGKDD Explorations: Special issue on Multi-Relational Data Mining 5(1), 31–48 (2003)

5. Dietterich, T., Getoor, L., Murphy, K. (eds.): Working Notes of the ICML-2004 Workshop on Statistical Relational Learning and its Connections to Other Fields, SRL 2004 (2004)

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