Wang, Pu, Domeniconi, Carlotta, Laskey, Kathryn, Latent Dirichlet Bayesian Co-Clustering, in: Machine Learning and Knowledge Discovery in Databases (2009), S. 522--537.
Shan, Hanhuai, Banerjee, Arindam: Bayesian Co-clustering.. In: ICDM : IEEE Computer Society, 2008, S. 530-539
Teh, Y. W., Kurihara, K., Welling, M.: Collapsed Variational Inference for {HDP}. 20. In: Advances in Neural Information Processing Systems, 2008
Vazquez, Alexei, Rezension zu: Bayesian approach to clustering real value, categorical and network data: solution via variational methods (2008).
Teh, Y.W., Jordan, M.I., Beal, M.J., Blei, D.M., {Hierarchical dirichlet processes}, in: Journal of the American Statistical Association 101 476 (2006), S. 1566--1581.
Banerjee, Arindam, Merugu, Srujana, Dhillon, Inderjit S., Ghosh, Joydeep, Clustering with Bregman Divergences., in: Journal of Machine Learning Research 6 (2005), S. 1705-1749.
Heinrich, G., {Parameter estimation for text analysis}, in: Web: http://www. arbylon. net/publications/text-est. pdf (2005).
Hertzmann, Aaron: Introduction to Bayesian learning. In: SIGGRAPH '04: ACM SIGGRAPH 2004 Course Notes. New York, NY, USA : ACM, 2004, S. 22
Murphy, Kevin, Rezension zu: An introduction to graphical models (2001).
Cowell, R., {Introduction to inference for Bayesian networks}, in: Learning in graphical models (1999), S. 9--26.
Jordan, Michael I., Ghahramani, Zoubin, Jaakkola, Tommi S., Saul, Lawrence K., An Introduction to Variational Methods for Graphical Models, in: Mach. Learn. 37 2 (1999), S. 183--233.
Cowell, R. {Advanced inference in Bayesian networks}.
Jordan, M. Learning in Graphical Models.
Jordan, M.I. {Learning in graphical models}.
Buntine, Wray L., Operations for Learning with Graphical Models, in: Journal of Artificial Intelligence Research 2 (1994), S. 159--225.
AN, S.G.E.M., AN, D.G.E.M., {Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images}, in: IEEE Trans. Pattern Anal. Machine Intell 6 (1984), S. 721--741.