Bull. Korean Math. Soc. 2016; 53(2): 589-600
Printed March 31, 2016
https://doi.org/10.4134/BKMS.2016.53.2.589
Copyright © The Korean Mathematical Society.
Sangwoon Yun
Sungkyunkwan University
In this paper, we propose a new incremental gradient method for solving a regularized minimization problem whose objective is the sum of $m$ smooth functions and a (possibly nonsmooth) convex function. This method uses an adaptive stepsize. Recently proposed incremental gradient methods for a regularized minimization problem need $O(mn)$ storage, where $n$ is the number of variables. This is the drawback of them. But, the proposed new incremental gradient method requires only $O(n)$ storage.
Keywords: incremental gradient method, nonsmooth, regularization, running average
MSC numbers: Primary 49M27, 49M37, 65K05, 90C25, 90C30
© 2022. The Korean Mathematical Society. Powered by INFOrang Co., Ltd