ProxSDP Documentation

ProxSDP is a semidefinite programming (SDP) solver based on the paper "Exploiting Low-Rank Structure in Semidefinite Programming by Approximate Operator Splitting". ProxSDP solves general SDP problems by means of a first order proximal algorithm based on the primal-dual hybrid gradient, also known as Chambolle-Pock method. The main advantage of ProxSDP over other state-of-the-art solvers is the ability of exploit the low-rank property inherent to several SDP problems.

Overview of problems ProxSDP can solve

• Any semidefinite programming problem in standard form;
• Semidefinite relaxations of nonconvex problems, e.g. max-cut, binary MIMO, optimal power flow, sensor localization;
• Nuclear norm minimization problems, e.g. matrix completion.

Installing

Currently ProxSDP only works with Julia 1.0.x

To add ProxSDP run:

pkg> add ProxSDP

Referencing

The first version of the paper can be found here.

@article{souto2018exploiting,
  title={Exploiting Low-Rank Structure in Semidefinite Programming by Approximate Operator Splitting},
  author={Souto, Mario and Garcia, Joaquim D and Veiga, {\'A}lvaro},
  journal={arXiv preprint arXiv:1810.05231},
  year={2018}
}