Convergence Properties of a Randomized Primal-Dual Algorithm with Applications to Parallel MRI

[1]  Jeffrey A. Fessler,et al.  Optimization Methods for Magnetic Resonance Image Reconstruction: Key Models and Optimization Algorithms , 2020, IEEE Signal Processing Magazine.

[2]  Pawel Markiewicz,et al.  Faster PET reconstruction with non-smooth priors by randomization and preconditioning , 2018, Physics in medicine and biology.

[3]  Panagiotis Patrinos,et al.  A New Randomized Block-Coordinate Primal-Dual Proximal Algorithm for Distributed Optimization , 2017, IEEE Transactions on Automatic Control.

[4]  Pascal Bianchi,et al.  A Coordinate-Descent Primal-Dual Algorithm with Large Step Size and Possibly Nonseparable Functions , 2015, SIAM J. Optim..

[5]  Antonin Chambolle,et al.  Stochastic Primal-Dual Hybrid Gradient Algorithm with Arbitrary Sampling and Imaging Applications , 2017, SIAM J. Optim..

[6]  Yangyang Xu,et al.  Randomized Primal–Dual Proximal Block Coordinate Updates , 2016, Journal of the Operations Research Society of China.

[7]  Antonin Chambolle,et al.  An introduction to continuous optimization for imaging , 2016, Acta Numerica.

[8]  Patrick L. Combettes,et al.  Stochastic Quasi-Fejér Block-Coordinate Fixed Point Iterations with Random Sweeping , 2014 .

[9]  Volkan Cevher,et al.  Convex Optimization for Big Data: Scalable, randomized, and parallel algorithms for big data analytics , 2014, IEEE Signal Processing Magazine.

[10]  Antonin Chambolle,et al.  A First-Order Primal-Dual Algorithm for Convex Problems with Applications to Imaging , 2011, Journal of Mathematical Imaging and Vision.

[11]  Tony F. Chan,et al.  A General Framework for a Class of First Order Primal-Dual Algorithms for Convex Optimization in Imaging Science , 2010, SIAM J. Imaging Sci..

[12]  L. Rudin,et al.  Nonlinear total variation based noise removal algorithms , 1992 .