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Inertial Proximal Incremental Aggregated Gradient Method by Zhang, Xiaoya; Peng, Wei; Zhang, Hui; Zhu, Wei is a scholarly article available to read on EtoBox.

What is Inertial Proximal Incremental Aggregated Gradient Method about?

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.

Author

Zhang, Xiaoya; Peng, Wei; Zhang, Hui; Zhu, Wei

Published

2017

Language

EN