| Bregman operator splitting with variable stepsize for total variation image reconstruction Y Chen, WW Hager, M Yashtini, X Ye, H Zhang Computational optimization and applications 54 (2), 317-342, 2013 | 73 | 2013 |
| A fast relaxed normal two split method and an effective weighted TV approach for Euler's elastica image inpainting M Yashtini, SH Kang SIAM Journal on Imaging Sciences 9 (4), 1552-1581, 2016 | 43 | 2016 |
| An alternating direction approximate Newton algorithm for ill-conditioned inverse problems with application to parallel MRI W Hager, C Ngo, M Yashtini, HC Zhang Journal of the Operations Research Society of China 3, 139-162, 2015 | 39 | 2015 |
| Solving complementarity and variational inequalities problems using neural networks M Yashtini, A Malek Applied Mathematics and Computation 190 (1), 216-230, 2007 | 38 | 2007 |
| A discrete-time neural network for solving nonlinear convex problems with hybrid constraints M Yashtini, A Malek Applied Mathematics and Computation 195 (2), 576-584, 2008 | 28 | 2008 |
| An Convergence Rate for the Variable Stepsize Bregman Operator Splitting Algorithm WW Hager, M Yashtini, H Zhang SIAM Journal on Numerical Analysis 54 (3), 1535-1556, 2016 | 26 | 2016 |
| Image fusion algorithms for color and gray level images based on LCLS method and novel artificial neural network A Malek, M Yashtini Neurocomputing 73 (4-6), 937-943, 2010 | 19 | 2010 |
| Convergence and rate analysis of a proximal linearized ADMM for nonconvex nonsmooth optimization M Yashtini Journal of Global Optimization 84 (4), 913-939, 2022 | 18 | 2022 |
| Alternating direction method of multiplier for Euler’s elastica-based denoising M Yashtini, SH Kang Scale Space and Variational Methods in Computer Vision: 5th International …, 2015 | 17 | 2015 |
| On the global convergence rate of the gradient descent method for functions with Hölder continuous gradients M Yashtini Optimization letters 10, 1361-1370, 2016 | 16 | 2016 |
| Multi-block nonconvex nonsmooth proximal admm: Convergence and rates under kurdyka–łojasiewicz property M Yashtini Journal of Optimization Theory and Applications 190 (3), 966-998, 2021 | 13 | 2021 |
| Partially parallel MR image reconstruction using sensitivity encoding M Yashtini, WW Hager, Y Chen, X Ye 2012 19th IEEE International Conference on Image Processing, 2077-2080, 2012 | 13 | 2012 |
| Efficient alternating minimization methods for variational edge-weighted colorization models M Yashtini, SH Kang, W Zhu Advances in Computational Mathematics 45, 1735-1767, 2019 | 8 | 2019 |
| Euler’s elastica-based algorithm for parallel MRI reconstruction using sensitivity encoding M Yashtini Optimization Letters 14 (6), 1435-1458, 2020 | 6 | 2020 |
| Convergence analysis of a proximal linearized ADMM algorithm for nonconvex nonsmooth optimization M Yashtini arXiv preprint arXiv:2009.05361, 2020 | 3 | 2020 |
| An O (1/K) convergence rate for the BOSVS algorithm in total variation regularized least squares problems W Hager, M Yashtini, H Zhang SIAM J. Numer. Anal, 2014 | 3 | 2014 |
| A neural network model for solving nonlinear optimization problems with real-time applications A Malek, M Yashtini Advances in Neural Networks–ISNN 2009: 6th International Symposium on Neural …, 2009 | 3 | 2009 |
| Alternating direction approximate Newton method for partially parallel imaging WW Hager, C Ngo, M Yashtini, H Zhang J. Oper. Res. Soc. China 3 (2), 139-162, 2015 | 1 | 2015 |
| Convergence rate of Bregman operator splitting with variable stepsize W Hager, M Yashtini, H Zhang SIAM J. Numer. Anal, 2013 | 1 | 2013 |
| Variable Metric Composite Proximal Alternating Linearized Minimization for Nonconvex Nonsmooth Optimization M Yashtini arXiv preprint arXiv:2209.06799, 2022 | | 2022 |
William HagerProfessor of Mathematics, University of FloridaE-mailová adresa ověřena na: ufl.edu
