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Learning in graphical models. Proceedings of the NATO ASI, Ettore Maiorana Centre, Erice, Italy, September 27 - October 7, 1996. (English) Zbl 0889.00024
NATO ASI Series. Series D. Behavioural and Social Sciences. 89. Dordrecht: Kluwer Academic Publishers. xi, 630 p. Dfl 520.00; $ 280.00; £177.00 (1998).

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The articles of this volume will be reviewed individually.
Indexed articles:
Cowell, Robert, Introduction to inference for Bayesian networks, 9-26 [Zbl 0948.62015]
Cowell, Robert, Advanced inference in Bayesian networks, 27-49 [Zbl 0948.62016]
Kjærulff, Uffe, Inference in Bayesian networks using nested junction trees, 51-74 [Zbl 0920.62036]
Dechter, R., Bucket elimination: A unifying framework for probabilistic inference, 75-104 [Zbl 0910.68209]
Jordan, Michael I.; Ghahramani, Zoubin; Jaakkola, Tommi S.; Saul, Lawrence K., An introduction to variational methods for graphical models, 105-161 [Zbl 0910.68175]
Jaakkola, Tommi S.; Jordan, Michael I., Improving the mean field approximation via the use of mixture distributions, 163-173 [Zbl 0953.60100]
Mackay, D. J. C., Introduction to Monte Carlo methods, 175-204 [Zbl 0911.65004]
Neal, Radford M., Suppressing random walks in Markov chain Monte Carlo using ordered overrelaxation, 205-228 [Zbl 0920.60055]
Richardson, Thomas S., Chain graphs and symmetric associations, 231-259 [Zbl 0926.62001]
Studený, M.; Vejnarová, J., The multi-information function as a tool for measuring stochastic dependence, 261-297 [Zbl 0917.60013]
Heckerman, David, A tutorial on learning with Bayesian networks, 301-354 [Zbl 0921.62029]
Neal, Radford M.; Hinton, Geoffrey E., A view of the EM algorithm that justifies incremental, sparse, and other variants, 355-368 [Zbl 0916.62019]
Bishop, Christopher M., Latent variable models, 371-403 [Zbl 0948.62043]
Buhmann, Joachim M., Stochastic algorithms for exploratory data analysis: Data clustering and data visualization, 405-419 [Zbl 0916.62002]
Friedman, Nir; Goldszmidt, Moises, Learning Bayesian networks with local structure, 421-459 [Zbl 0910.68176]
Geiger, Dan; Heckerman, David; Meek, Christopher, Asymptotic model selection for directed networks with hidden variables, 461-477 [Zbl 0910.68177]
Hinton, Geoffrey E.; Sallans, Brian; Ghahramani, Zoubin, A hierarchical community of experts, 479-494 [Zbl 0910.68210]
Kearns, Michael; Mansour, Yishay; Ng, Andrew Y., An information-theoretic analysis of hard and soft assignment methods for clustering, 495-520 [Zbl 0910.68178]
Monti, Stefano; Cooper, Gregory F., Learning hybrid Bayesian networks from data, 521-540 [Zbl 0910.68179]
Saul, Lawrence; Jordan, Michael, A mean field learning algorithm for unsupervised neural networks, 541-554 [Zbl 0910.68180]
Smith, Peter W. F.; Whittaker, Joe, Edge exclusion tests for graphical Gaussian models, 555-574 [Zbl 0940.62052]
Spiegelhalter, D. J.; Best, N. G.; Gilks, W. R.; Inskip, H., Hepatitis B: A case study in MCMC, 575-598 [Zbl 1054.62608]
Williams, C. K. I., Prediction with Gaussian processes: From linear regression to linear prediction and beyond, 599-621 [Zbl 0921.62121]

00B25 Proceedings of conferences of miscellaneous specific interest
60-06 Proceedings, conferences, collections, etc. pertaining to probability theory
62-06 Proceedings, conferences, collections, etc. pertaining to statistics
65-06 Proceedings, conferences, collections, etc. pertaining to numerical analysis
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