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math.NA2023
Preconditioner Design via the Bregman Divergence
Andreas Bock, Martin S. Andersen
We study a preconditioner for a Hermitian positive definite linear system, which is obtained as the solution of a matrix nearness problem based on the Bregman log determinant diver…
math.ST2023
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…