-
1
-
-
0000501656
-
Information theory and an extension of the maximum likelihood principle
-
B. Petrox & F. Caski (Eds.), Budapest: Akademiai Kiado
-
Akaike, H. (1973). Information theory and an extension of the maximum likelihood principle. In B. Petrox & F. Caski (Eds.), Proceedings of the second international symposium on information theory (pp. 267-281). Budapest: Akademiai Kiado.
-
(1973)
Proceedings of the Second International Symposium on Information Theory
, pp. 267-281
-
-
Akaike, H.1
-
2
-
-
0001019707
-
Learning bayesian networks is NP-Complete
-
D. Fisher & H. Lenz (Eds.), Springer-Verlag
-
Chickering, D. (1996). Learning Bayesian networks is NP-Complete. In D. Fisher & H. Lenz (Eds.), Learning from data: Artificial intelligence and statistics v (pp. 121-130). Springer-Verlag.
-
(1996)
Learning from Data: Artificial Intelligence and Statistics V
, pp. 121-130
-
-
Chickering, D.1
-
3
-
-
0000582742
-
Statistical theory: The prequential approach
-
Dawid, A. (1984). Statistical theory: The prequential approach. Journal of the Royal Statistical Society A, 147, 278-292.
-
(1984)
Journal of the Royal Statistical Society A
, vol.147
, pp. 278-292
-
-
Dawid, A.1
-
4
-
-
34249761849
-
Learning bayesian networks: The combination of knowledge and statistical data
-
Heckerman, D., Geiger, D., & Chickering, D. (1995). Learning Bayesian networks: The combination of knowledge and statistical data. Machine Learning, 20 (3), 197-243.
-
(1995)
Machine Learning
, vol.20
, Issue.3
, pp. 197-243
-
-
Heckerman, D.1
Geiger, D.2
Chickering, D.3
-
5
-
-
34347261665
-
A lineartime algorithm for computing the multinomial stochastic complexity
-
Kontkanen, P., & Myllym̈aki, P. (2007). A lineartime algorithm for computing the multinomial stochastic complexity. Information Processing Letters, 103 (6), 227-233.
-
(2007)
Information Processing Letters
, vol.103
, Issue.6
, pp. 227-233
-
-
Kontkanen, P.1
Myllym̈aki, P.2
-
7
-
-
0029777083
-
Fisher information and stochastic complexity
-
Rissanen, J. (1996). Fisher information and stochastic complexity. IEEE Transactions on Information Theory, 42 (1), 40-47.
-
(1996)
IEEE Transactions on Information Theory
, vol.42
, Issue.1
, pp. 40-47
-
-
Rissanen, J.1
-
10
-
-
0000120766
-
Estimating the dimension of a model
-
Schwarz, G. (1978). Estimating the dimension of a model. Annals of Statistics, 6, 461-464.
-
(1978)
Annals of Statistics
, vol.6
, pp. 461-464
-
-
Schwarz, G.1
-
11
-
-
0023380770
-
Universal sequential coding of single messages
-
Shtarkov, Y. (1987). Universal sequential coding of single messages. Problems of Information Transmission, 23, 3-17.
-
(1987)
Problems of Information Transmission
, vol.23
, pp. 3-17
-
-
Shtarkov, Y.1
-
12
-
-
70350678796
-
On sensitivity of the MAP Bayesian network structure to the equivalent sample size parameter
-
R. Parr & L. van der Gaag (Eds.), AUAI Press
-
Silander, T., Kontkanen, P., & Myllym̈aki, P. (2007). On sensitivity of the MAP Bayesian network structure to the equivalent sample size parameter. In R. Parr & L. van der Gaag (Eds.), Proceedings of the 23rd conference on uncertainty in artificial intelligence (pp. 360-367). AUAI Press.
-
(2007)
Proceedings of the 23rd Conference on Uncertainty in Artificial Intelligence
, pp. 360-367
-
-
Silander, T.1
Kontkanen, P.2
Myllym̈aki, P.3
-
13
-
-
80053201441
-
A simple approach for finding the globally optimal Bayesian network structure
-
R. Dechter & T. Richardson (Eds.), AUAI Press
-
Silander, T., & Myllym̈aki, P. (2006). A simple approach for finding the globally optimal Bayesian network structure. In R. Dechter & T. Richardson (Eds.), Proceedings of the 22nd conference on uncertainty in artificial intelligence (pp. 445- 452). AUAI Press.
-
(2006)
Proceedings of the 22nd Conference on Uncertainty in Artificial Intelligence
, pp. 445-452
-
-
Silander, T.1
Myllym̈aki, P.2
-
14
-
-
77955228820
-
Factorized normalized maximum likelihood criterion for learning Bayesian network structures
-
Hirtshals, Denmark
-
Silander, T., Roos, T., Kontkanen, P., & Myllym̈aki, P. (2008). Factorized normalized maximum likelihood criterion for learning Bayesian network structures. In Proceedings of the 4th European workshop on probabilistic graphical models (PGM-08) (pp. 257-264). Hirtshals, Denmark.
-
(2008)
Proceedings of the 4th European Workshop on Probabilistic Graphical Models (PGM-08)
, pp. 257-264
-
-
Silander, T.1
Roos, T.2
Kontkanen, P.3
Myllym̈aki, P.4
-
15
-
-
85156264409
-
On the dirichlet prior and bayesian regularization
-
Vancouver, Canada: MIT Press
-
Steck, H., & Jaakkola, T. S. (2002). On the Dirichlet prior and Bayesian regularization. In Advances in neural information processing systems 15 (pp. 697-704). Vancouver, Canada: MIT Press.
-
(2002)
Advances in Neural Information Processing Systems
, vol.15
, pp. 697-704
-
-
Steck, H.1
Jaakkola, T.S.2
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