1. School of Mathematics, Northwest University, Xi’an 710069, China
2. Academy of Mathematics and System Sciences, Chinese Academy of Sciences, Beijing 100190, China
3. College of Computer Information Engineering, Jiangxi Normal University, Nanchang 330022, China
Abstract This paper focuses on the feature extraction and variable selection of massive data which is divided and stored in different linked computers, and studies the distributed $L_{1/2}$ regularization. Based on Alternating Direction Method of Multipliers algorithm(ADMM), distributed $L_{1/2}$ regularization algorithm which communicates information between the neighborhood computers has been proposed and the convergence of the algorithm has been proved. The variable selection results of the approach are the same with the entire data set by using $L_{1/2}$ regularization. Numerical studies show that this method is both effective and practical which performs well in distributed data analysis.
Received: 18 September 2016
Published: 07 April 2018
WANG Pu-yu, ZHANG Hai, ZENG Jin-shan. The distributed $L_{1/2}$ regularization. Applied Mathematics A Journal of Chinese Universities, 2017, 32(3): 332-342.
