The non-log-concave marginal likelihood of Bayesian variable selection admits global optimization via a DC algorithm with linear convergence under mild conditions.
and McCulloch, Robert E
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A Bayesian framework with adaptive elastic nets and variational EM infers Gaussian graphical models from high-dimensional data with reliable FDR control and good power on heterogeneous graphs.
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Revisiting Bayesian Variable Selection via Optimization
The non-log-concave marginal likelihood of Bayesian variable selection admits global optimization via a DC algorithm with linear convergence under mild conditions.
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A Bayesian framework with adaptive elastic nets for the inference of Gaussian graphical models
A Bayesian framework with adaptive elastic nets and variational EM infers Gaussian graphical models from high-dimensional data with reliable FDR control and good power on heterogeneous graphs.