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Best Pair Formulation & Accelerated Scheme for Non-convex Principal Component Pursuit
Type
ArticleKAUST Department
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) DivisionApplied Mathematics and Computational Science Program
Computer Science Program
Date
2020Permanent link to this record
http://hdl.handle.net/10754/660274.1
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Given two disjoint sets, the best pair problem aims to find a point in one set and another point in the other set with minimal distance between them. In this paper, we formulate the classical robust principal component analysis (RPCA) problem as a best pair problem and design an accelerated proximal gradient algorithm to solve it. We prove that the method enjoys global convergence with a local linear rate. Our extensive numerical experiments on both real and synthetic data sets suggest that our proposed algorithm outperforms relevant baseline algorithms in the literature.Publisher
IEEEarXiv
1905.10598Additional Links
https://ieeexplore.ieee.org/document/9145595/https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9145595
ae974a485f413a2113503eed53cd6c53
10.1109/TSP.2020.3011024