Robust iteratively reweighted SIMPLS
Sign Up to like & getrecommendations! Published in 2017 at "Journal of Chemometrics"
DOI: 10.1002/cem.2881
Abstract: Partial least squares regression is a very powerful multivariate regression technique to model multicollinear data or situation where the number of explanatory variables is larger than the sample size. Two algorithms, namely, Non‐linear Iterative Partial… read more here.
Keywords: reweighted simpls; least squares; iteratively reweighted; robust iteratively ... See more keywords
An iteratively reweighted least-squares approach to adaptive robust adjustment of parameters in linear regression models with autoregressive and t-distributed deviations
Sign Up to like & getrecommendations! Published in 2017 at "Journal of Geodesy"
DOI: 10.1007/s00190-017-1062-6
Abstract: In this paper, we investigate a linear regression time series model of possibly outlier-afflicted observations and autocorrelated random deviations. This colored noise is represented by a covariance-stationary autoregressive (AR) process, in which the independent error… read more here.
Keywords: reweighted least; regression; linear regression; iteratively reweighted ... See more keywords
Image Denoising and Refinement Based on an Iteratively Reweighted Least Squares Filter
Sign Up to like & getrecommendations! Published in 2020 at "KSCE Journal of Civil Engineering"
DOI: 10.1007/s12205-020-2103-x
Abstract: This paper presents a method to reduce noise and refine detail features of a scene based on an iteratively reweighted least squares method. The performance of the proposed filter, called the iteratively reweighted least squares… read more here.
Keywords: reweighted least; least squares; based iteratively; iteratively reweighted ... See more keywords
On an iteratively reweighted linesearch based algorithm for nonconvex composite optimization
Sign Up to like & getrecommendations! Published in 2023 at "Inverse Problems"
DOI: 10.1088/1361-6420/acca43
Abstract: In this paper we propose a new algorithm for solving a class of nonsmooth nonconvex problems, which is obtained by combining the iteratively reweighted scheme with a finite number of forward–backward iterations based on a… read more here.
Keywords: linesearch based; iteratively reweighted; based algorithm; nonconvex composite ... See more keywords
An Efficient Estimation and Classification Methods for High Dimensional Data Using Robust Iteratively Reweighted SIMPLS Algorithm Based on nu-Support Vector Regression
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DOI: 10.1109/access.2021.3066172
Abstract: The statistically inspired modification of the partial least squares (SIMPLS) is the most commonly used algorithm to solve a partial least squares regression problem when the number of explanatory variables ( $p$ ) is larger… read more here.
Keywords: regression; reweighted simpls; iteratively reweighted; support vector ... See more keywords
An Iteratively Reweighted Instrumental-Variable Estimator for Robust 3-D AOA Localization in Impulsive Noise
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Transactions on Signal Processing"
DOI: 10.1109/tsp.2019.2931210
Abstract: This paper considers the problem of robust three-dimensional (3-D) angle-of-arrival (AOA) source localization in the presence of impulsive $\alpha$-stable noise based on the $l_p$-norm minimization criterion. The iteratively reweighted least-squares algorithm (IRLS) is a well-known… read more here.
Keywords: tex math; inline formula; iteratively reweighted;
Proximal iteratively reweighted algorithm for low-rank matrix recovery
Sign Up to like & getrecommendations! Published in 2018 at "Journal of Inequalities and Applications"
DOI: 10.1186/s13660-017-1602-x
Abstract: This paper proposes a proximal iteratively reweighted algorithm to recover a low-rank matrix based on the weighted fixed point method. The weighted singular value thresholding problem gains a closed form solution because of the special… read more here.
Keywords: reweighted algorithm; iteratively reweighted; rank matrix; low rank ... See more keywords
Convergence and stability of iteratively reweighted least squares for low-rank matrix recovery
Sign Up to like & getrecommendations! Published in 2017 at "Inverse Problems and Imaging"
DOI: 10.3934/ipi.2017030
Abstract: In this paper, we study the theoretical properties of iteratively reweighted least squares algorithm for recovering a matrix (IRLS-M for short) from noisy linear measurements. The IRLS-M was proposed by Fornasier et al. (2011) [… read more here.
Keywords: begin document; reweighted least; least squares; iteratively reweighted ... See more keywords