Iteratively reweighted least squares

Known as: IRLS, Iterative weighted least squares, Iteratively weighted least squares 
The method of iteratively reweighted least squares (IRLS) is used to solve certain optimization problems with objective functions of the form: by an… (More)
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2018
2018
In this paper, we propose a novel algorithm for analysis-based sparsity reconstruction. It can solve the generalized problem by… (More)
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2016
2016
Principal component analysis (PCA) is often used to reduce the dimension of data by selecting a few orthonormal vectors that… (More)
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2014
2014
In this paper, we propose a novel algorithm for structured sparsity reconstruction. This algorithm is based on the iterative… (More)
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2014
2014
Registration of point sets is done by finding a rotation and translation that produces a best fit between a set of data points… (More)
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Highly Cited
2013
Highly Cited
2013
In this paper, we first study q minimization and its associated iterative reweighted algorithm for recovering sparse vectors… (More)
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Highly Cited
2013
Highly Cited
2013
In this paper, we first study q minimization and its associated iterative reweighted algorithm for recovering sparse vectors… (More)
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Highly Cited
2011
Highly Cited
2011
We present and analyze an efficient implementation of an iteratively reweighted least squares algorithm for recovering a matrix… (More)
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Highly Cited
2010
Highly Cited
2010
The scope of application of iteratively reweighted least squares to statistical estimation problems is considerably wider than is… (More)
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2009
2009
An implementation of the weighted least absolute value (WLAV) method for obtaining an estimate of the state of the power system… (More)
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1980
1980
A description of a system of subroutines to compute solutions to the iteratively reweighted least squares problem is presented… (More)
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