410 citations · 713 across the 33 of their papers we have counts for
7 papers · 1 filter
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…
A Symmetry-Preserving Tensor -SVD
Victor Arsenescu, Misha E. Kilmer
Multiway data such as image collections and video is ubiquitous, but the usual approach of flattening them into matrices discards the cross-mode structure that often carries the si…
Wavelet-based multilevel framework for -regularized image deblurring
Danyh Tolah, Malena I. Español, Misha E. Kilmer
Solving large-scale -regularized image deblurring problems efficiently while preserving sharp edges remains a significant computational challenge. We propose a wavelet-base…
Structure-Informed Bounds on the Kronecker Rank of Block-Structured Matrices
Allison Fuller, Malena Español, Misha Kilmer
We derive theoretical bounds on the Kronecker rank of block-structured matrices that possess both inner and outer structure. Building on the matrix-to-tensor and tensor-to-matrix f…
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 -…
Exact Symmetry as Algebra: Group-Structured Tensors that Enforce Physical Selection Rules
Paulina Hoyos, Shashanka Ubaru, Dongsung Huh +5
Symmetry determines which physical responses of molecules and crystals are allowed and underlies many models used throughout the physical sciences. Yet several widely used machine-…
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…