7 citations · 13 across the 21 of their papers we have counts for
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A provably convergent MM-GKS variant for large-scale inverse problems
Mirjeta Pasha, Eric de Sturler, Misha Kilmer
For high-quality images with sharp edges, a popular choice for edge-preserving regularization is using a general(ized) -norm of the gradient of the image. This can be imple…
Randomized Tucker-Sketched GMRES
Alberto Bucci, Martina Iannacito, Mirjeta Pasha +1
We address the problem of solving large-scale tensor-structured linear systems in the Tucker format. In this setting, standard iterative solvers such as GMRES face a fundamental bo…
A Sketched Generalized Krylov Subspace Method for Large-Scale Regularization
Davide Palitta, Mirjeta Pasha
The generalized Krylov subspace (GKS) method is an effective projection technique for large-scale Tikhonov regularization with a general regularization matrix. As the subspace expa…
Nonlinear RMM-GKS for Large-Scale Dynamic and Streaming Inverse Problems with Uncertain Forward Operators
Toluwani Okunola, Mirjeta Pasha, Misha E. Kilmer +2
Many practical imaging systems suffer from uncertainty in acquisition geometry -- such as projection angles in computed tomography or sensor positions in photoacoustic tomography -…
An Efficient Cumulative Edge-Detection Method for Image Reconstruction
Toluwani Okunola, Mirjeta Pasha, Misha E. Kilmer
When reconstructing images from noisy measurements, such as in medical scans or scientific imaging, we face an inverse problem: recovering an unknown image from indirect, corrupted…
Efficient Sketching-Based Summation of Tucker Tensors
Rudi Smith, Mirjeta Pasha, Andrés Galindo-Olarte +5
We present efficient, sketching-based methods for the summation of tensors in Tucker format. Leveraging the algebraic structure of Khatri-Rao and Kronecker products, our approach e…
Hybrid ABBA-GMRES for Unmatched Backprojectors in Large Scale X-Ray Computerized Tomography
Ryan Bentley, Mirjeta Pasha, Malena Sabaté Landman +2
In large-scale X-ray computed tomography (CT), matrix-free iterative methods are essential due to the prohibitive cost of explicitly forming the system matrix. In practice, forward…
A Scalable Sequential Framework for Dynamic Inverse Problems via Model Parameter Estimation
Aryeh Keating, Mirjeta Pasha
Large-scale dynamic inverse problems are often ill-posed due to model complexity and the high dimensionality of the unknown parameters. Regularization is commonly employed to mitig…