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Mixed precision Rayleigh quotient iteration for total least squares problems
With the recent emergence of mixed precision hardware, there has been a renewed interest in its use for solving numerical linear algebra problems...
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A new structured spectral conjugate gradient method for nonlinear least squares problems
Least squares models appear frequently in many fields, such as data fitting, signal processing, machine learning, and especially artificial...
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Estimating error norms in CG-like algorithms for least-squares and least-norm problems
In Meurant et al. (Numer. Algorithms 88 (3), 1337–1359,
2021 ), we presented an adaptive estimate for the energy norm of the error in the conjugate...
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A two-dimensional randomized extended Gauss-Seidel algorithm for solving least squares problems
We study a two-dimensional coordinate descent method to solve large linear least squares problems expanding on the method presented by Leventhal and...
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Approximating sparse Hessian matrices using large-scale linear least squares
Large-scale optimization algorithms frequently require sparse Hessian matrices that are not readily available. Existing methods for approximating...
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An improved multi-task least squares twin support vector machine
In recent years, multi-task learning (MTL) has become a popular field in machine learning and has a key role in various domains. Sharing knowledge...
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A hybrid smoothed moving least-squares interpolation method for acoustic scattering problems
The discrete model in the traditional finite element method (FEM) inevitably behaves more stiffly than the corresponding continuous model. This...
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Componentwise Least Squares Support Vector Machines
This chapter describes componentwise Least Squares Support Vector Machines (LS-SVMs) for the estimation of additive models consisting of a sum of...
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Logarithmic Least Squares Method
In this chapter, we present logarithmic least squares method (LLSM) for priority for incomplete fuzzy reciprocal preference relations. LLSM method is...
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Image classification based on weighted nonconvex low-rank and discriminant least squares regression
Classifiers based on least squares regression (LSR) are effective in multi-classification tasks. However, there are two main problems that greatly...
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ECT for flow imaging: total least squares for image reconstruction algorithm
For the problem that noise has a great impact on the measurement data during the electrical capacitance tomography data acquisition process, a...
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Variable selection using axis-aligned random projections for partial least-squares regression
In high-dimensional data modeling, variable selection plays a crucial role in improving predictive accuracy and enhancing model interpretability...
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Locally sparse and robust partial least squares in scalar-on-function regression
We present a novel approach for estimating a scalar-on-function regression model, leveraging a functional partial least squares methodology. Our...
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A least squares twin support vector machine method with uncertain data
Twin support vector machine (TWSVM) learns two nonparallel hyperplanes for binary class classification problems. It assumes that the training data...
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Penalized Least Squares Classifier: Classification by Regression Via Iterative Cost-Sensitive Learning
Least squares estimate that can directly obtain the analytical solution to minimize the mean square error (MSE) is one of the most effective...
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Quality-related Fault Detection Based on Approximate Kernel Partial Least Squares Method
The kernel partial least squares (KPLS) method has been widely used in quality-related fault detection since it can acquire the features of the...
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Fuzzy Least Squares Support Vector Machine with Fuzzy Hyperplane
This study uses fuzzy set theory for least squares support vector machines (LS-SVM) and proposes a novel formulation that is called a fuzzy...
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Exploring oversampling in RBF least-squares collocation method of lines for surface diffusion
This paper investigates the numerical behavior of the radial basis functions least-squares collocation (RBF-LSC) method of lines (MoL) for solving...
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Least squares structural twin bounded support vector machine on class scatter
Several projects and application development teams are spending their precious time and energy in the field of classification and regression. So, the...
