Variational EM Algorithms for Non-Gaussian Latent Variable Models

Part of Advances in Neural Information Processing Systems 18 (NIPS 2005)

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Jason Palmer, Kenneth Kreutz-Delgado, Bhaskar Rao, David Wipf


We consider criteria for variational representations of non-Gaussian latent variables, and derive variational EM algorithms in general form. We establish a general equivalence among convex bounding methods, evidence based methods, and ensemble learning/Variational Bayes methods, which has previously been demonstrated only for particular cases.