Dirichlet enhanced relational learning

ICML 2005 - Proceedings of the 22nd International Conference on Machine Learning

Volumn , Issue , 2005, Pages 1009-1016

  Xu, Zhao ^a   Tresp, Volker ^b   Yu, Kai ^b   Shipeng, Yu S ^a   Kriegel, Hans Peter ^a,b  

^a UNIVERSITY OF MUNICH   (Germany)

^b SIEMENS AG   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

KNOWLEDGE ACQUISITION; MATHEMATICAL MODELS; PARAMETER ESTIMATION; PROBABILITY; SYSTEMS ANALYSIS;

HIERARCHICAL BAYESIAN APPROACH; MODEL PARAMETERS; RELATIONAL LEARNING;

LEARNING SYSTEMS;

EID: 31844451004     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (13)

1. Dzeroski, S., & Lavrac, N. (Eds.). (2001). Relational data mining. Berlin: Springer.
2. Escobar, M. D., & West, M. (1998). Computing bayesian nonparametric hierarchical models (Technical Report 92-A20). Duke University, ISDS.
3. Friedman, N., Getoor, L. Koller, D., & Pfeffer, A. (1999). Learning probabilistic relational models. Proc. 16th JCAI (pp. 1300-1309). Morgan Kaufmann.
4. Gelman, A., Carlin, J. B., Stern, H. S., & Rubin, D. B. (2003). Bayesian data analysis. CRC press.
5. Getoor, L., Friedman, N., Koller, D., & Taskar, B. (2003). Learning probabilistic models of link structure. Journal of Machine Learning Research, 3, 679-707.
6. Heckerman, D., Meek, C., & Koller, D. (2004). Probabilistic models for relational data (Technical Report MSR-TR-2004-30). Microsoft.
7. Jelinek, F. (1997). Statistical methods for speech recognition. Cambridge, MA, USA: MIT Press.
8. Raedt, L. D., & Kersting, K. (2003). Probabilistic logic learning. SIGKDD Explor. Newsl., 5, 31-48.
9. Teh, Y. W., Jordan, M. I., Beal, M. J., & Blei, D. M. (2004). Hierarchical dirichlet processes (Technical Report 653). UC Berkeley Statistics.
10. Tresp, V., & Yu, K. (2004). An introduction to nonparametric hierarchical bayesian modelling with a focus on multi-agent learning. In Proc. the hamilton summer school on switching and learning in feedback systems, 290-312. Springer.
11. Ullman, J. D., & Widom, J. (1997). A first course in database systems. Upper Saddle River,NJ,USA: Prentice Hall.
12. Wrobel, S. (2001). Inductive logic programming for knowledge discovery in databases. In S. Dzeroski and N. Lavrac (Eds.), Relational data mining, 74-101. Springer.
13. Yu, K., Tresp, V., & Yu, S. (2004). A nonparametric hierarchical bayesian framework for information filtering. Proc. 27th SIGIR (pp. 353-360). ACM.