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• W2613304467 abstract "In this paper we address the problem of sparse representation (SR) within a Bayesian framework. We assume that the observations are generated from a Bernoulli-Gaussian process and consider the corresponding Bayesian inference problem. Tractable solutions are then proposed based on the “meanfield” approximation and the variational Bayes EM algorithm. The resulting SR algorithms are shown to have a tractable complexity and very good performance over a wide range of sparsity levels. In particular, they significantly improve the critical sparsity upon state-of-the-art SR algorithms." @default.
• W2613304467 created "2017-05-19" @default.
• W2613304467 creator A5006637829 @default.
• W2613304467 date "2012-01-01" @default.
• W2613304467 modified "2023-09-23" @default.
• W2613304467 title "Sparse Representation Algorithms Based on Mean-Field Approximations" @default.
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