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Improved Image Quality for Static BLADE Magnetic Resonance Imaging Using the Total-Variation Regularized Least Absolute Deviation Solver [PDF]
In order to improve the image quality of BLADE magnetic resonance imaging (MRI) using the index tensor solvers and to evaluate MRI image quality in a clinical setting, we implemented BLADE MRI reconstructions using two tensor solvers (the least-squares ...
Hsin-Chia Chen +9 more
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Constrained least absolute deviation neural networks. [PDF]
It is well known that least absolute deviation (LAD) criterion or L(1)-norm used for estimation of parameters is characterized by robustness, i.e., the estimated parameters are totally resistant (insensitive) to large changes in the sampled data. This is an extremely useful feature, especially, when the sampled data are known to be contaminated by ...
Wang Z, Peterson BS.
europepmc +4 more sources
Novel Global Harmony Search Algorithm for Least Absolute Deviation [PDF]
The method of least absolute deviation (LAD) finds applications in many areas, due to its robustness compared to the least squares regression (LSR) method. LAD is robust in that it is resistant to outliers in the data.
Longquan Yong
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Leveraged least trimmed absolute deviations [PDF]
AbstractThe design of regression models that are not affected by outliers is an important task which has been subject of numerous papers within the statistics community for the last decades. Prominent examples of robust regression models are least trimmed squares (LTS), where theklargest squared deviations are ignored, and least trimmed absolute ...
Nathan Sudermann-Merx, Steffen Rebennack
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If there is multicollinearity and outliers in the data, the inference about parameter estimation in the LS method will deviate due to the inefficiency of this method in estimating.
Netti Herawati +2 more
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Direct Least Absolute Deviation Fitting of Ellipses [PDF]
Scattered data from edge detection usually involve undesired noise which seriously affects the accuracy of ellipse fitting. In order to alleviate this kind of degradation, a method of direct least absolute deviation ellipse fitting by minimizing the ℓ1 algebraic distance is presented.
Gang Zhou +3 more
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Least Absolute Deviation Support Vector Regression [PDF]
Least squares support vector machine (LS‐SVM) is a powerful tool for pattern classification and regression estimation. However, LS‐SVM is sensitive to large noises and outliers since it employs the squared loss function. To solve the problem, in this paper, we propose an absolute deviation loss function to reduce the effects of outliers and derive a ...
Wang, Kuaini +3 more
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Geometry of deviation measures for triangular distributions
Triangular distributions are widely used in many applications with limited sample data, business simulations, and project management. As with other distributions, a standard way to measure deviations is to compute the standard deviation.
Yuhe Wang, Eugene Pinsky
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Analysis of least absolute deviation [PDF]
SUMMARY We develop a unified L 1 -based analysis-of-variance-type method for testing linear hypotheses. Like the classical L2-based analysis of variance, the method is coordinate-free in the sense that it is invariant under any linear transformation of the covariates or regression parameters.
Chen, Kani +3 more
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Gaussian and Lerch Models for Unimodal Time Series Forcasting
We consider unimodal time series forecasting. We propose Gaussian and Lerch models for this forecasting problem. The Gaussian model depends on three parameters and the Lerch model depends on four parameters.
Azzouz Dermoune +2 more
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