Inertial Proximal Incremental Aggregated Gradient Method
Optimization and Control
2017-12-19 v2
Abstract
In this paper, we introduce an inertial version of the Proximal Incremental Aggregated Gradient method (PIAG) for minimizing the sum of smooth convex component functions and a possibly nonsmooth convex regularization function. Theoretically, we show that the inertial Proximal Incremental Aggregated Gradiend (iPIAG) method enjoys a global linear convergence under a quadratic growth condition, which is strictly weaker than strong convexity, provided that the stepsize is not larger than a constant. Moreover, we present two numerical expreiments which demonstrate that iPIAG outperforms the original PIAG.
Cite
@article{arxiv.1712.00984,
title = {Inertial Proximal Incremental Aggregated Gradient Method},
author = {Xiaoya Zhang and Wei Peng and Hui Zhang and Wei Zhu},
journal= {arXiv preprint arXiv:1712.00984},
year = {2017}
}
Comments
17 pages, 3 figures