3 papers
math.NA2017
Conjugate gradient based acceleration for inverse problems
Sergey Voronin, Christophe Zaroli, Naresh P. Cuntoor
The conjugate gradient method is a widely used algorithm for the numerical solution of a system of linear equations. It is particularly attractive because it allows one to take adv…
stat.CO2016
Randomized Matrix Decompositions using R
N. Benjamin Erichson, Sergey Voronin, Steven L. Brunton +1
Matrix decompositions are fundamental tools in the area of applied mathematics, statistical computing, and machine learning. In particular, low-rank matrix decompositions are vital…
math.NA2015
An Iteratively Reweighted Least Squares Algorithm for Sparse Regularization
Sergey Voronin, Ingrid Daubechies
We present a new algorithm and the corresponding convergence analysis for the regularization of linear inverse problems with sparsity constraints, applied to a new generalized spar…