LAUSR

About LAUSR
Donate
Contact Us

Follow us:

You are not signed in:

Sign Up!


   Articles with "proposed methods" as a keyword



Non-iterative explicit integration algorithms based on acceleration time history for nonlinear dynamic systems

Sign Up to like & get
recommendations! Published in 2019 at "Archive of Applied Mechanics"

DOI: 10.1007/s00419-019-01616-y

Abstract: A two-step explicit acceleration integration method (EAIM2) and a three-step explicit acceleration integration method (EAIM3), which are entirely explicit time integration algorithms, are proposed based on acceleration time history. The computation efforts and costs can… read more here.

Keywords: proposed methods; integration; acceleration; time ... See more keywords

Globally convergent three-term conjugate gradient projection methods for solving nonlinear monotone equations

Sign Up to like & get
recommendations! Published in 2018 at "Arabian Journal of Mathematics"

DOI: 10.1007/s40065-018-0206-8

Abstract: In this paper, we propose two derivative-free conjugate gradient projection methods for systems of large-scale nonlinear monotone equations. The proposed methods are shown to satisfy the sufficient descent condition. Furthermore, the global convergence of the… read more here.

Keywords: monotone equations; proposed methods; gradient projection; nonlinear monotone ... See more keywords

Stochastic feature selection with annealing and its applications to streaming data

Sign Up to like & get
recommendations! Published in 2025 at "Journal of Nonparametric Statistics"

DOI: 10.1080/10485252.2025.2456767

Abstract: Feature selection is an important topic in high-dimensional statistics and machine learning, for prediction and understanding the underlying phenomena. It has many applications in computer vision, natural language processing, bioinformatics, etc. However, most feature selection… read more here.

Keywords: stochastic feature; selection methods; proposed methods; selection ... See more keywords

Auto-Encoders Derivatives on Different Occluded Face Images: Comprehensive Review and New Results

Sign Up to like & get
recommendations! Published in 2025 at "IEEE Access"

DOI: 10.1109/access.2025.3632159

Abstract: This paper presents a novel approach for improving occluded face recognition performance using a family of autoencoders (AE) architectures. The proposed structures include four stages: image preprocessing, feature extraction using autoencoder derivatives, classification via a… read more here.

Keywords: autoencoder; convolutional autoencoder; occluded face; proposed methods ... See more keywords

Stationary and Sparse Denoising Approach for Corticomuscular Causality Estimation

Sign Up to like & get
recommendations! Published in 2024 at "IEEE Transactions on Biomedical Engineering"

DOI: 10.1109/tbme.2024.3518602

Abstract: Objective: Cortico-muscular communication patterns are instrumental in understanding movement control. Estimating significant causal relationships between motor cortex electroencephalogram (EEG) and surface electromyogram (sEMG) from concurrently active muscles presents a formidable challenge since the relevant processes… read more here.

Keywords: methodology; proposed methods; causality; measurement noise ... See more keywords

Convolutional Sparse Coding for Compressed Sensing CT Reconstruction

Sign Up to like & get
recommendations! Published in 2019 at "IEEE Transactions on Medical Imaging"

DOI: 10.1109/tmi.2019.2906853

Abstract: Over the past few years, dictionary learning (DL)-based methods have been successfully used in various image reconstruction problems. However, the traditional DL-based computed tomography (CT) reconstruction methods are patch-based and ignore the consistency of pixels… read more here.

Keywords: reconstruction; coding compressed; proposed methods; sparse coding ... See more keywords

Minimax Optimal Bandits for Heavy Tail Rewards.

Sign Up to like & get
recommendations! Published in 2022 at "IEEE transactions on neural networks and learning systems"

DOI: 10.1109/tnnls.2022.3203035

Abstract: Stochastic multiarmed bandits (stochastic MABs) are a problem of sequential decision-making with noisy rewards, where an agent sequentially chooses actions under unknown reward distributions to minimize cumulative regret. The majority of prior works on stochastic… read more here.

Keywords: regret; proposed methods; minimax optimal; exploration ... See more keywords

Weighted Joint Sentiment-Topic Model for Sentiment Analysis Compared to ALGA: Adaptive Lexicon Learning Using Genetic Algorithm

Sign Up to like & get
recommendations! Published in 2022 at "Computational Intelligence and Neuroscience"

DOI: 10.1155/2022/7612276

Abstract: Latent Dirichlet Allocation (LDA) is an approach to unsupervised learning that aims to investigate the semantics among words in a document as well as the influence of a subject on a word. As an LDA-based… read more here.

Keywords: sentiment; topic; proposed methods; sentiment topic ... See more keywords

Modified prism methods for measuring the refractive index of solid and liquid substances

Sign Up to like & get
recommendations! Published in 2023 at "Computer Optics"

DOI: 10.18287/2412-6179-co-1230

Abstract: Methods for measuring the refractive index of optically transparent dielectric materials are considered. Modified methods based on the methods of minimum deviation and constant deviation are proposed and allow determining the refractive index of triangular… read more here.

Keywords: measuring refractive; proposed methods; refractive index; prism ... See more keywords

Computer tools for the construction and analysis of some efficient root-finding simultaneous methods

Sign Up to like & get
recommendations! Published in 2020 at "Filomat"

DOI: 10.2298/fil2007151p

Abstract: Using the tools provided by computer algebra system Mathematica, we consider two iterative methods of high efficiency for the simultaneous approximation of simple or multiple (real or complex) zeros of algebraic polynomials. The proposed methods… read more here.

Keywords: computer tools; simultaneous methods; convergence; order ... See more keywords

Estimation of Distribution Algorithms with Fuzzy Sampling for Stochastic Programming Problems

Sign Up to like & get
recommendations! Published in 2020 at "Applied Sciences"

DOI: 10.3390/app10196937

Abstract: Generating practical methods for simulation-based optimization has attracted a great deal of attention recently. In this paper, the estimation of distribution algorithms are used to solve nonlinear continuous optimization problems that contain noise. One common… read more here.

Keywords: stochastic programming; proposed methods; estimation distribution; programming problems ... See more keywords