Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Convergence Properties of a Randomized Primal-Dual Algorithm with
  Applications to Parallel MRI   The Stochastic Primal-Dual Hybrid Gradient (SPDHG) was proposed by Chambolle
et al. (2018) and is an efficient algorithm to solve some nonsmooth large-scale
optimization problems. In this paper we prove its almost sure convergence for
convex but not necessarily strongly convex functionals. We also look into its
application to parallel Magnetic Resonance Imaging reconstruction in order to
test performance of SPDHG. Our numerical results show that for a range of
settings SPDHG converges significantly faster than its deterministic
counterpart.

22
The categories of this paper are: chao-dyn
9
The categories of this paper are: nlin
24
The categories of this paper are: dg-ga
25
The categories of this paper are: patt-sol
0
The categories of this paper are: hep-ph
28
The categories of this paper are: alg-geom
21
The categories of this paper are: adap-org
26
The categories of this paper are: bayes-an
14
The categories of this paper are: math-ph
35
The categories of this paper are: mtrl-th
20
The categories of this paper are: acc-phys
7
The categories of this paper are: hep-th
8
The categories of this paper are: hep-ex
13
The categories of this paper are: quant-ph
34
The categories of this paper are: chem-ph
27
The categories of this paper are: comp-gas