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Bibliography

1
B. Bouzy.
Mathematical morphology applied to computer go.
IJPRAI, 17(2), 2003.

2
T. Graepel D. Stern and D. MacKay.
Modelling uncertainty in the game of Go.
In Proc. of the Conference on Neural Information Processing Systems, Vancouver, December 2004.

3
G.E. Hinton.
Modelling high-dimensional data by combining simple experts.
In Proc. AAAI-2000, Austin, Texas.

4
M. Jordan, Z. Ghahramani, T. Jaakkola, and L. Saul.
An introduction to variational methods for graphical models.
In M. Jordan, editor, Learning in Graphical Models, pages 105-161. The MIT Press, Cambridge, MA, USA, 1999.

5
M. Müller.
Computer Go.
Special issue on games of Artificial Intelligence Journal, 2001.

6
J. Pearl.
Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference.
Morgan Kaufmann Publishers Inc., San Francisco, CA, USA, 1988.

7
L. De Raedt and K. Kersting.
Probabilistic logic learning.
ACM-SIGKDD Explorations, special issue on Multi-Relational Data Mining, 5(1):31-48, July 2003.

8
T. Raiko.
The go-playing program called Go81.
In Proceedings of the Finnish Artificial Intelligence Conference, STeP 2004, pages 197-206, Helsinki, Finland, 2004.

9
B. Taskar, P. Abbeel, and D. Koller.
Discriminative probabilistic models for relational data.
In Proc. Conference on Uncertainty in Artificial Intelligence (UAI02), Edmonton, 2002.

10
H. Valpola, A. Honkela, M. Harva, A. Ilin, T. Raiko, and T. Östman.
Bayes blocks software library.
http://www.cis.hut.fi/projects/bayes/software/, 2003.

11
H. Valpola, T. Östman, and J. Karhunen.
Nonlinear independent factor analysis by hierarchical models.
In Proc. ICA2003, pages 257-262, Nara, Japan, 2003.

12
H. Valpola, T. Raiko, and J. Karhunen.
Building blocks for hierarchical latent variable models.
In Proc. ICA2001, pages 710-715, San Diego, USA, 2001.



Tapani Raiko 2005-06-17