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Variational Inference in Nonconjugate Models
Variational inference Nonconjugat emodels Laplace approximations The delta method
2012/11/22
Mean-field variational inference is widely used for approximate posterior inference in many probabilistic models. When the model is conditionally conjugate, variational updates are in closed-form. How...
Efficient variational inference in large-scale Bayesian compressed sensing
large-scale Bayesian variational inference Computer Vision and Pattern Recognition
2011/10/9
Abstract: We study linear models under heavy-tailed priors from a probabilistic viewpoint. Instead of computing a single sparse most probable (MAP) solution as in standard deterministic approaches, th...
Variational inference for Dirichlet process mixtures
Dirichlet processes hierarchical models variational inference image processing Bayesian computation
2009/9/21
Dirichlet process (DP) mixture models are the cornerstone of non-
parametric Bayesian statistics, and the development of Monte-Carlo Markov chain
(MCMC) sampling methods for DP mixtures has enabled ...