Author

Mirjeta Pasha

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Preprint Sep 2026

A provably convergent MM-GKS variant for large-scale inverse problems

For high-quality images with sharp edges, a popular choice for edge-preserving regularization is using a general(ized) $\ell_q$-norm of the gradient of the image. This can be implemented efficiently using the $\ell_2$-norm and a sequence of weighted gradients, with weights derived from the current solution estimate. We...

Mirjeta Pasha, E. de Sturler, M. Kilmer · 0 citations

Preprint Aug 2026

Randomized Tucker-Sketched GMRES

Two randomized algorithms within the sketched GMRES framework that replace full Arnoldi orthogonalization with short recurrences are proposed, providing robustness across a wide range of problems and outperform standard low-rank Tucker solvers in symmetric and non-symmetric settings.

Alberto Bucci, Martina Iannacito, Mirjeta Pasha et al. · 0 citations