A parameterized proximal point algorithm for separable convex optimization

@article{Bai2018APP,
  title={A parameterized proximal point algorithm for separable convex optimization},
  author={J. Bai and Hongchao Zhang and Jicheng Li},
  journal={Optimization Letters},
  year={2018},
  volume={12},
  pages={1589-1608}
}
In this paper, we develop a parameterized proximal point algorithm (P-PPA) for solving a class of separable convex programming problems subject to linear and convex constraints. The proposed algorithm is provable to be globally convergent with a worst-case O(1 / t) convergence rate, where t denotes the iteration number. By properly choosing the algorithm parameters, numerical experiments on solving a sparse optimization problem arising from statistical learning show that our P-PPA could perform… Expand
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