A primal-dual type algorithm with the O(1/t) convergence rate for large scale constrained convex programs

@article{Yu2016APT,
  title={A primal-dual type algorithm with the O(1/t) convergence rate for large scale constrained convex programs},
  author={Hao Yu and Michael J. Neely},
  journal={2016 IEEE 55th Conference on Decision and Control (CDC)},
  year={2016},
  pages={1900-1905}
}
This paper considers large scale constrained convex programs. These are often difficult to solve by interior point methods or other Newton-type methods due to the prohibitive computation and storage complexity for Hessians or matrix inversions. Instead, large scale constrained convex programs are often solved by gradient based methods or decomposition based methods. The conventional primal-dual subgradient method, also known as the Arrow-Hurwicz-Uzawa subgradient method, is a low complexity… CONTINUE READING