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Continuous Iteratively Reweighted Least Squares Algorithm for Solving Linear Models by Convex Relaxation

Continuous Iteratively Reweighted Least Squares Algorithm for Solving Linear Models by Convex Relaxation
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摘要 In this paper, we present continuous iteratively reweighted least squares algorithm (CIRLS) for solving the linear models problem by convex relaxation, and prove the convergence of this algorithm. Under some conditions, we give an error bound for the algorithm. In addition, the numerical result shows the efficiency of the algorithm. In this paper, we present continuous iteratively reweighted least squares algorithm (CIRLS) for solving the linear models problem by convex relaxation, and prove the convergence of this algorithm. Under some conditions, we give an error bound for the algorithm. In addition, the numerical result shows the efficiency of the algorithm.
出处 《Advances in Pure Mathematics》 2019年第6期523-533,共11页 理论数学进展(英文)
关键词 Linear Models CONTINUOUS Iteratively Reweighted Least SQUARES CONVEX RELAXATION Principal COMPONENT Analysis Linear Models Continuous Iteratively Reweighted Least Squares Convex Relaxation Principal Component Analysis
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