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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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Generalising combinatorial discriminant analysis through conditioning truncated Rayleigh flow
Fisher’s Linear Discriminant Analysis (LDA) has been widely used for linear classification, feature selection, and metrics learning in multivariate...
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Local Spectral for Polarized Communities Search in Attributed Signed Network
Signed networks are graphs with edge annotations to indicate whether each interaction is friendly (positive edge) or antagonistic (negative edge)....
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A Resolvent Quasi-Monte Carlo Method for Estimating the Minimum Eigenvalues Using the Error Balancing
There are iterative Monte Carlo (MC) methods that can be used for estimating the extreme eigenvalues of large dimensional matrices. The Power MC...
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RPH-PGD: Randomly Projected Hessian for Perturbed Gradient Descent
The perturbed gradient descent (PGD) method, which adds random noises in the search directions, has been widely used in solving large-scale...
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A simple extrapolation method for clustered eigenvalues
This paper introduces a simple variant of the power method. It is shown analytically and numerically to accelerate convergence to the dominant...
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A mixed precision LOBPCG algorithm
The locally optimal block preconditioned conjugate gradient (LOBPCG) algorithm is a popular approach for computing a few smallest eigenvalues and the...
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Design and Implementation of the Optimized Computing Architecture for Matrix Decomposition Algorithms
This paper will take the recursive CORDIC computing unit developed in our laboratory as the main computing core. The computing data is arranged in...
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Implicit algorithms for eigenvector nonlinearities
We study and derive algorithms for nonlinear eigenvalue problems, where the system matrix depends on the eigenvector, or several eigenvectors (or...
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First Principal Eigenvector
In this chapter, I present a unified framework to derive and discuss ten adaptive algorithms (some well-known) for principal eigenvector computation,...
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A τ-preconditioner for a non-symmetric linear system arising from multi-dimensional Riemann-Liouville fractional diffusion equation
In this paper, we study a τ -preconditioner for non-symmetric linear system arising from a steady-state multi-dimensional Riemann-Liouville (RL)...
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The Optimal Layer of User-Specific Reconfigurable Intelligent Surfaces Structure for Uplink Communication System
Reconfigurable intelligent surfaces (RIS) can be utilized for enhancing the communication quality, and are regarded as a promising six-generation...
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A Krylov-Schur-like method for computing the best rank-(r1,r2,r3) approximation of large and sparse tensors
The paper is concerned with methods for computing the best low multilinear rank approximation of large and sparse tensors. Krylov-type methods have...
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Principal Component Analysis over the Boolean Circuit Within TFHE Scheme
In today’s information-driven world, the need to protect personal data while maintaining efficient data processing capabilities is crucial....
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A novel approach to perform linear discriminant analyses for a 4-way alzheimer’s disease diagnosis based on an integration of pearson’s correlation coefficients and empirical cumulative distribution function
Diagnosing Alzheimer’s disease (AD) remains a significant challenge, particularly in effectively identifying individuals in the early (EMCI) and late...
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A rotated shift-splitting method for complex symmetric linear systems
This article proposes a generalized rotated shift-splitting (GRSS) iterative method for solving complex symmetric linear systems. Our analysis...
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A Comparative Study of Graph Matching Algorithms in Computer Vision
The graph matching optimization problem is an essential component for many tasks in computer vision, such as bringing two deformable objects in...
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Parallel implementations of randomized vector algorithm for solving large systems of linear equations
The results of a parallel implementation of a randomized vector algorithm for solving systems of linear equations are presented in the paper. The...
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Global convergence of Negative Correlation Extreme Learning Machine
Ensemble approaches introduced in the Extreme Learning Machine literature mainly come from methods that rely on data sampling procedures, under the...
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Enhancing PAPR performance in MIMO-OFDM system using hybrid optimal MMSE-MLSE equalizers
Wireless communication technologies are playing a very important role in the modern world. The use of multiple antennas with orthogonal frequency...
