S. Voronin

发表

Regularization of Linear Systems with Sparsity Constraints with Applications to Large Scale Inverse Problems

S. Voronin, 2012 .

Convolution based smooth approximations to the absolute value function with application to non-smooth regularization

S. Voronin, Gorkem G. Ozkaya, Davis Yoshida, 2014 .

Solving or resolving global tomographic models with spherical wavelets, and the scale and sparsity of seismic heterogeneity

Guust Nolet, S. Voronin, Ignace Loris, 2011 .

A variational problem in the hydrodynamics of open channels

G. Atanov, S. Voronin, 1980 .

Solving large tomographic linear systems: size reduction and error estimation

G. Nolet, S. Voronin, D. Mikesell, 2014 .

Gradient Based Methods for Non-Smooth Regularization Via Convolution Smoothing

S. Voronin, Davis Yoshida, Gorkem Ozkaya, 2014, 1408.6795.

Introduction to Numerical Approaches for Forward and Inverse Heat Transfer Problems

S. Voronin, 2020 .

Randomized Matrix Decompositions using R pdf

Steven L. Brunton, J. Nathan Kutz, N. Benjamin Erichson, 2016, Journal of Statistical Software.

Solving or resolving global tomographic models with spherical wavelets, and the scale and sparsity of seismic heterogeneity

S. Voronin, Ignace Loris, Frederik J. Simons, 2010, 1104.3151.

A Randomized Blocked Algorithm for Efficiently Computing Rank-revealing Factorizations of Matrices

Per-Gunnar Martinsson, Sergey Voronin, P. Martinsson, 2015, SIAM J. Sci. Comput..

Efficient algorithms for cur and interpolative matrix decompositions

Per-Gunnar Martinsson, Sergey Voronin, P. Martinsson, 2014, Adv. Comput. Math..

Conjugate gradient based acceleration for inverse problems

Naresh P. Cuntoor, Sergey Voronin, Christophe Zaroli, 2017, 1709.03092.

Compression approaches for the regularized solutions of linear systems from large-scale inverse problems

Sergey Voronin, Guust Nolet, Dylan Mikesell, 2014, 1404.5684.

Survey of Computational Methods for Inverse Problems

Sergey Voronin, Christophe Zaroli, S. Voronin, 2018, Recent Trends in Computational Science and Engineering.

A new generalized thresholding algorithm for inverse problems with sparsity constraints

Rick Chartrand, Sergey Voronin, R. Chartrand, 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.

RSVDPACK: Subroutines for computing partial singular value decompositions via randomized sampling on single core, multi core, and GPU architectures pdf

Per-Gunnar Martinsson, Sergey Voronin, P. Martinsson, 2015, ArXiv.

Global seismic tomography with sparsity constraints: Comparison with smoothing and damping regularization

Ignace Loris, Ingrid Daubechies, Frederik J. Simons, 2013 .

YAMPA: Yet Another Matching Pursuit Algorithm for compressive sensing

Waheed U. Bajwa, Sergey Voronin, Muhammad A. Lodhi, 2016, SPIE Commercial + Scientific Sensing and Imaging.

An Iteratively Reweighted Least Squares Algorithm for Sparse Regularization

Ingrid Daubechies, Sergey Voronin, I. Daubechies, 2015, 1511.08970.

RSVDPACK: An implementation of randomized algorithms for computing the singular value, interpolative, and CUR decompositions of matrices on multi-core and GPU architectures

Per-Gunnar Martinsson, Sergey Voronin, P. Martinsson, 2015 .

A CUR Factorization Algorithm based on the Interpolative Decomposition pdf

Per-Gunnar Martinsson, Sergey Voronin, P. Martinsson, 2014, ArXiv.

Clustering and presorting for parallel burrows wheeler-based compression

Raqibul Hasan, Eugene Borovikov, Sergey Voronin, 2021, Int. J. Model. Simul. Sci. Comput..