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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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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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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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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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A new numerical algorithm based on least squares method for solving stochastic Itô-Volterra integral equations
In conjunction with least squares method and generalized hat functions, we propose a new algorithm for stochastic Itô-Volterra integral equations....
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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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Fast Global Image Smoothing via Quasi Weighted Least Squares
Image smoothing is a long-studied research area with tremendous approaches proposed. However, how to perform high-quality image smoothing with less...
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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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Recursive least squares method for training and pruning convolutional neural networks
Convolutional neural networks (CNNs) have shown good performance in many practical applications. However, their high computational and storage...
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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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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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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 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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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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Enhanced moving least squares method for solving the stochastic fractional Volterra integro-differential equations of Hammerstein type
One of the challenging and practical issues that have recently attracted the attention of researchers is stochastic equations. One of the important...
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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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Depth from Focus using Windowed Linear Least Squares Regressions
We present a novel depth from focus technique. Following prior work, our pipeline starts with a focal stack and an estimation of the amount of...
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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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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...
