Stochastic Accelerated Alternating Direction Method of Multipliers with Importance Sampling

Chenxi Chen (), Yunmei Chen (), Yuyuan Ouyang () and Eduardo Pasiliao ()
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Chenxi Chen: University of Florida
Yunmei Chen: University of Florida
Yuyuan Ouyang: Clemson University
Eduardo Pasiliao: AFB

Journal of Optimization Theory and Applications, 2018, vol. 179, issue 2, No 13, 676-695

Abstract: Abstract In this paper, we incorporate importance sampling strategy into accelerated framework of stochastic alternating direction method of multipliers for solving a class of stochastic composite problems with linear equality constraint. The rates of convergence for primal residual and feasibility violation are established. Moreover, the estimation of variance of stochastic gradient is improved due to the use of important sampling. The proposed algorithm is capable of dealing with the situation, where the feasible set is unbounded. The experimental results indicate the effectiveness of the proposed method.

Keywords: Stochastic ADMM; Duality gap; Variance estimation; Importance sampling; 90C06; 90C25; 90C30 (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s10957-018-1270-0

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