2009

Wang, P.; Domeniconi, C. & Laskey, K.: Latent Dirichlet Bayesian Co-Clustering. In: Machine Learning and Knowledge Discovery in Databases (2009), S. 522-537
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2008

Shan, H. & Banerjee, A.: Bayesian Co-clustering.. ICDM. IEEE Computer Society, 2008, S. 530-539
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Teh, Y. W.; Kurihara, K. & Welling, M.: Collapsed Variational Inference for HDP. Advances in Neural Information Processing Systems. 2008 (20)
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Vazquez, A.: Bayesian approach to clustering real value, categorical and network data: solution via variational methods. , 2008
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2006

Teh, Y.; Jordan, M.; Beal, M. & Blei, D.: Hierarchical dirichlet processes. In: Journal of the American Statistical Association 101 (2006), Nr. 476, S. 1566-1581
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2005

Banerjee, A.; Merugu, S.; Dhillon, I. S. & Ghosh, J.: Clustering with Bregman Divergences.. In: Journal of Machine Learning Research 6 (2005), S. 1705-1749
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Heinrich, G.: Parameter estimation for text analysis. In: Web: http://www. arbylon. net/publications/text-est. pdf (2005),
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2004

Hertzmann, A.: Introduction to Bayesian learning. SIGGRAPH '04: ACM SIGGRAPH 2004 Course Notes. New York, NY, USA: ACM, 2004, S. 22
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2001

Murphy, K.: An introduction to graphical models. , 2001
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1999

Cowell, R.: Introduction to inference for Bayesian networks. In: Learning in graphical models (1999), S. 9-26
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Jordan, M. I.; Ghahramani, Z.; Jaakkola, T. S. & Saul, L. K.: An Introduction to Variational Methods for Graphical Models. In: Mach. Learn. 37 (1999), Nr. 2, S. 183-233
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1998

Cowell, R.: Advanced inference in Bayesian networks. Learning in Graphical Models. MIT Press, 1998
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Jordan, M. (Hrsg.): Learning in Graphical Models. MIT Press, 1998
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Jordan, M.: Learning in graphical models. Kluwer Academic Publishers, 1998
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1994

Buntine, W. L.: Operations for Learning with Graphical Models. In: Journal of Artificial Intelligence Research 2 (1994), S. 159-225
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1984

AN, S. & AN, D.: Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images. In: IEEE Trans. Pattern Anal. Machine Intell 6 (1984), S. 721-741
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