Acta mathematica scientia,Series A ›› 2015, Vol. 35 ›› Issue (6): 1136-1145.

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A Modified Proximal Gradient Method and Its Convergence Rate

Li Yingyi, Zhang Haibin, Gao Huan   

  1. College of Applied Sciences, Beijing University of Technology, Beijing 100124
  • Received:2014-10-14 Revised:2015-04-27 Online:2015-12-25 Published:2015-12-25

Abstract:

In this paper, a modified proximal gradient method is proposed for solving a class of nonsmooth convex optimization problems, which arises in many contemporary statistical and signal applications. The proposed method adopts the self-adaptive stepsize. In addition, it is linearly convergent without the assumption of the strong convexity of the objective function.

Key words: Nonsmooth convex optimization, Modified proximal gradient method, Linear convergence

CLC Number: 

  • O224
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