3 citations · 3 across the 7 of their papers we have counts for
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The Geometry and Well-Posedness of Sparse Regularized Linear Regression
Jasper Marijn Everink, Yiqiu Dong, Martin Skovgaard Andersen
In this work, we study the well-posedness of certain sparse regularized linear regression problems, i.e., the existence, uniqueness and continuity of the solution map with respect…
Sparse Bayesian Inference with Regularized Gaussian Distributions
Jasper Marijn Everink, Yiqiu Dong, Martin Skovgaard Andersen
Regularization is a common tool in variational inverse problems to impose assumptions on the parameters of the problem. One such assumption is sparsity, which is commonly promoted…
Bayesian Inference with Projected Densities
Jasper Marijn Everink, Yiqiu Dong, Martin Skovgaard Andersen
Constraints are a natural choice for prior information in Bayesian inference. In various applications, the parameters of interest lie on the boundary of the constraint set. In this…