1 citations · 1 across the 2 of their papers we have counts for
5 papers
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…
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 -…
Recycling MMGKS for large-scale dynamic and streaming data
Mirjeta Pasha, Eric de Sturler, Misha E. Kilmer
Reconstructing high-quality images with sharp edges requires the use of edge-preserving constraints in the regularized form of the inverse problem. The use of the -norm on…
Subspace Recycling for Sequences of Shifted Systems with Applications in Image Recovery
Misha E. Kilmer, Eric de Sturler
For many applications involving a sequence of linear systems with slowly changing system matrices, subspace recycling, which exploits relationships among systems and reuses search…
Stopping Criteria for the Conjugate Gradient Algorithm in High-Order Finite Element Methods
Yichen Guo, Eric de Sturler, Tim Warburton
We consider stopping criteria that balance algebraic and discretization errors for the conjugate gradient algorithm applied to high-order finite element discretizations of Poisson…