-
1
-
-
84874743878
-
Predictive neural networks for traffic disturbance detection in the telephone network
-
Lille, France
-
Y. Bennani and F. Bossaert. 1996. Predictive neural networks for traffic disturbance detection in the telephone network. In Proceedings of IMACS-CESA'96, page xx, Lille, France.
-
(1996)
Proceedings of IMACS-CESA'96
-
-
Bennani, Y.1
Bossaert, F.2
-
2
-
-
0042883436
-
Efficient Approximation for the Marginal Likelihood of Incomplete Data given a Bayesian Network
-
Morgan Kaufmann
-
D. Chickering and D. Heckerman. 1996. Efficient Approximation for the Marginal Likelihood of Incomplete Data given a Bayesian Network. In UAI'96, pages 158-168. Morgan Kaufmann.
-
(1996)
UAI'96
, pp. 158-168
-
-
Chickering, D.1
Heckerman, D.2
-
3
-
-
0038517651
-
Finding optimal bayesian networks
-
Adnan Darwiche and Nir Friedman, editors S.F., Cal. Morgan Kaufmann Publishers
-
D. Chickering and C. Meek. 2002. Finding optimal bayesian networks. In Adnan Darwiche and Nir Friedman, editors, Proceedings of the 18th Conference on Uncertainty in Artificial Intelligence (UAI-02), pages 94-102, S.F., Cal. Morgan Kaufmann Publishers.
-
(2002)
Proceedings of the 18th Conference on Uncertainty in Artificial Intelligence (UAI-02)
, pp. 94-102
-
-
Chickering, D.1
Meek, C.2
-
5
-
-
84933530882
-
Approximating discrete probability distributions with dependence trees
-
C.K. Chow and C.N. Liu. 1968. Approximating discrete probability distributions with dependence trees. IEEE Transactions on Information Theory, 14(3):462-467.
-
(1968)
IEEE Transactions on Information Theory
, vol.14
, Issue.3
, pp. 462-467
-
-
Chow, C.K.1
Liu, C.N.2
-
6
-
-
9244243116
-
Semisupervised learning of classifiers: Theory, algorithms, and their application to human-computer interaction
-
I. Cohen, F. G. Cozman, N. Sebe, M. C. Cirelo, and T. S. Huang. 2004. Semisupervised learning of classifiers: Theory, algorithms, and their application to human-computer interaction. IEEE Transactions on Pattern Analysis and Machine Intelligence, 26(12):1553-1568.
-
(2004)
IEEE Transactions on Pattern Analysis and Machine Intelligence
, vol.26
, Issue.12
, pp. 1553-1568
-
-
Cohen, I.1
Cozman, F.G.2
Sebe, N.3
Cirelo, M.C.4
Huang, T.S.5
-
9
-
-
0031269184
-
On the optimal-ity of the simple bayesian classifier under zero-one loss
-
P. Domingos and M. Pazzani. 1997. On the optimal-ity of the simple bayesian classifier under zero-one loss. Machine Learning, 29:103-130.
-
(1997)
Machine Learning
, vol.29
, pp. 103-130
-
-
Domingos, P.1
Pazzani, M.2
-
11
-
-
0001586968
-
Learning belief networks in the presence of missing values and hidden variables
-
Morgan Kaufmann
-
N. Friedman. 1997. Learning belief networks in the presence of missing values and hidden variables. In Proceedings of the 14th International Conference on Machine Learning, pages 125-133. Morgan Kaufmann.
-
(1997)
Proceedings of the 14th International Conference on Machine Learning
, pp. 125-133
-
-
Friedman, N.1
-
12
-
-
0000854197
-
The bayesian structural em algorithm
-
Gregory F. Cooper and Serafín Moral, editors San Francisco, July. Morgan Kaufmann
-
N. Friedman. 1998. The bayesian structural EM algorithm. In Gregory F. Cooper and Serafín Moral, editors, Proceedings of the 14th Conference on Uncertainty in Artificial Intelligence (UAI-98), pages 129-138, San Francisco, July. Morgan Kaufmann.
-
(1998)
Proceedings of the 14th Conference on Uncertainty in Artificial Intelligence (UAI-98)
, pp. 129-138
-
-
Friedman, N.1
-
14
-
-
0021518209
-
Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images
-
November
-
S. Geman and D. Geman. 1984. Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images. IEEE Transactions on Pattern Analysis and Machine Intelligence, 6(6):721-741, November.
-
(1984)
IEEE Transactions on Pattern Analysis and Machine Intelligence
, vol.6
, Issue.6
, pp. 721-741
-
-
Geman, S.1
Geman, D.2
-
16
-
-
34249761849
-
Learning Bayesian networks: The combination of knowledge and statistical data
-
D. Heckerman, D. Geiger, and M. Chickering. 1995. Learning Bayesian networks: The combination of knowledge and statistical data. Machine Learning, 20:197-243.
-
(1995)
Machine Learning
, vol.20
, pp. 197-243
-
-
Heckerman, D.1
Geiger, D.2
Chickering, M.3
-
17
-
-
58149210716
-
The em algorithm for graphical association models with missing data
-
S. Lauritzen. 1995. The EM algorithm for graphical association models with missing data. Computational Statistics and Data Analysis, 19:191-201.
-
(1995)
Computational Statistics and Data Analysis
, vol.19
, pp. 191-201
-
-
Lauritzen, S.1
-
21
-
-
0036532762
-
Learning recursive bayesian multinets for data clustering by means of constructive induction
-
J.M. Peña, J. Lozano, and P. Larrañaga. 2002. Learning recursive bayesian multinets for data clustering by means of constructive induction. Machine Learning, 47:1:63-90.
-
(2002)
Machine Learning
, vol.47
, Issue.1
, pp. 63-90
-
-
Peña, J.M.1
Lozano, J.2
Larrañaga, P.3
-
22
-
-
0003250080
-
Parameter estimation in Bayesian networks from incomplete databases
-
M. Ramoni and P. Sebastiani. 1998. Parameter estimation in Bayesian networks from incomplete databases. Intelligent Data Analysis, 2:139-160.
-
(1998)
Intelligent Data Analysis
, vol.2
, pp. 139-160
-
-
Ramoni, M.1
Sebastiani, P.2
-
23
-
-
0043198674
-
Robust learning with missing data
-
M. Ramoni and P. Sebastiani. 2000. Robust learning with missing data. Machine Learning, 45:147-170.
-
(2000)
Machine Learning
, vol.45
, pp. 147-170
-
-
Ramoni, M.1
Sebastiani, P.2
-
24
-
-
0017133178
-
Inference and missing data
-
D.B. Rubin. 1976. Inference and missing data. Biometrika, 63:581-592.
-
(1976)
Biometrika
, vol.63
, pp. 581-592
-
-
Rubin, D.B.1
-
26
-
-
84986980101
-
Sequential updating of conditional probabilities on directed graphical structures
-
D. J. Spiegelhalter and S. L. Lauritzen. 1990. Sequential updating of conditional probabilities on directed graphical structures. Networks, 20:579-605.
-
(1990)
Networks
, vol.20
, pp. 579-605
-
-
Spiegelhalter, D.J.1
Lauritzen, S.L.2
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