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Continuous Iteratively Reweighted Least Squares Algorithm for Solving Linear Models by Convex Relaxation
Department of Mathematics, College of Science, Shanghai University, Shanghai, China
Department of Mathematics, College of Science, Shanghai University, Shanghai, China
- 1 Department of Mathematics, College of Science, Shanghai University, Shanghai, China
- 2 Department of Mathematics, College of Science, Shanghai University, Shanghai, China
Advances in Pure Mathematics·Volume 09 (2019)·Pages 523–533·Published 27 June 2019·DOI10.4236/apm.2019.96024
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Abstract
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.
KeywordsLinear ModelsContinuous Iteratively Reweighted Least SquaresConvex RelaxationPrincipal Component Analysis
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