Linear least squares (mathematics)

Known as: Constrained regression, Constrained linear least squares, Normal equations 
In statistics and mathematics, linear least squares is an approach fitting a mathematical or statistical model to data in cases where the idealized… (More)
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Highly Cited
2013
Highly Cited
2013
PURPOSE Linear least squares estimators are widely used in diffusion MRI for the estimation of diffusion parameters. Although… (More)
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Highly Cited
2011
Highly Cited
2011
HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they… (More)
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Highly Cited
2011
Highly Cited
2011
We present a new algorithm for linear spectral mixture analysis, which is capable of supervised unmixing of hyperspectral data… (More)
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Highly Cited
2009
Highly Cited
2009
The affine rank minimization problem, which consists of finding a matrix of minimum rank subject to linear equality constraints… (More)
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Highly Cited
2007
Highly Cited
2007
This work addresses the problem of regularized linear least squares (RLS) with non-quadratic separable regularization. Despite… (More)
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Highly Cited
2006
Highly Cited
2006
MOTIVATION Many practical pattern recognition problems require non-negativity constraints. For example, pixels in digital images… (More)
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Highly Cited
2001
Highly Cited
2001
Linear spectral mixture analysis (LSMA) is a widely used technique in remote sensing to estimate abundance fractions of materials… (More)
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Highly Cited
1997
Highly Cited
1997
In this paper a modification of the standard algorithm for non-negativity-constrained linear least squares regression is proposed… (More)
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Highly Cited
1997
Highly Cited
1997
The total least squares (TLS) method is a successful method for noise reduction in linear least squares problems in a number of… (More)
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Highly Cited
1996
Highly Cited
1996
We introduce two new temporal difference (TD) algorithms based on the theory of linear least-squares function approximation. We… (More)
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