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   Articles with "kernel" as a keyword



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Comparative analysis of the kernel types in generalized autocalibrating partially parallel acquisition algorithms for accelerated three‐dimensional magnetic resonance spectroscopic imaging data

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recommendations! Published in 2022 at "International Journal of Imaging Systems and Technology"

DOI: 10.1002/ima.22624

Abstract: This study was conducted to comparatively analyze the performance of generalized autocalibrating partially parallel acquisition (GRAPPA) algorithms according to the kernel types, which has not yet been reported. A GRAPPA algorithm using one 3D kernel… read more here.

Keywords: autocalibrating partially; partially parallel; kernel types; kernel ... See more keywords
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Numerical simulation of telegraph and Cattaneo fractional‐type models using adaptive reproducing kernel framework

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recommendations! Published in 2020 at "Mathematical Methods in the Applied Sciences"

DOI: 10.1002/mma.6998

Abstract: In this article, a class of generalized telegraph and Cattaneo time‐fractional models along with Robin's initial‐boundary conditions is considered using the adaptive reproducing kernel framework. Accordingly, a relatively novel numerical treatment is introduced to investigate… read more here.

Keywords: reproducing kernel; kernel framework; adaptive reproducing; kernel ... See more keywords
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Linear and Kernel Model Construction Methods for Predicting Drug-Target Interactions in a Chemogenomic Framework.

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recommendations! Published in 2018 at "Methods in molecular biology"

DOI: 10.1007/978-1-4939-8639-2_12

Abstract: Identification of drug-target interactions is a crucial process in drug discovery. In this chapter, we present protocols for recent advancements in machine learning methods for predicting drug-target interactions from heterogeneous biological data in a chemogenomic… read more here.

Keywords: kernel; target; methods predicting; drug ... See more keywords
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A combination of CSP-based method with soft margin SVM classifier and generalized RBF kernel for imagery-based brain computer interface applications

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recommendations! Published in 2020 at "Multimedia Tools and Applications"

DOI: 10.1007/s11042-020-08675-2

Abstract: Several methods utilizing common spatial pattern (CSP) algorithm have been presented for improving the identification of imagery movement patterns for brain computer interface applications. The present study focuses on improving a CSP-based algorithm for detecting… read more here.

Keywords: imagery; kernel; svm; computer interface ... See more keywords
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Using Locality Preserving Projections to Improve the Performance of Kernel Clustering

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recommendations! Published in 2020 at "Neural Processing Letters"

DOI: 10.1007/s11063-020-10252-5

Abstract: Many clustering methods may have poor performance when the data structure is complex (i.e., the data has an aspheric shape or non-linear relationship). Inspired by this view, we proposed a clustering model which combines kernel function… read more here.

Keywords: locality preserving; kernel; performance; preserving projections ... See more keywords
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A Kernel Connectivity-based Outlier Factor Algorithm for Rare Data Detection in a Baking Process

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recommendations! Published in 2018 at "IFAC-PapersOnLine"

DOI: 10.1016/j.ifacol.2018.09.316

Abstract: Abstract Due to strict legislation on greenhouse gas emission reduction, energy intensive industries include the bakery industry are all under pressure to improve the energy efficiency in the manufacturing processes. In this paper, an energy… read more here.

Keywords: kernel; outlier factor; energy; based outlier ... See more keywords
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Testing-optimal kernel choice in HAR inference

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recommendations! Published in 2020 at "Journal of Econometrics"

DOI: 10.1016/j.jeconom.2020.06.007

Abstract: Abstract The paper investigates the optimal kernel choice in heteroskedasticity and autocorrelation robust tests based on the fixed-b asymptotics. In parallel with the optimality of the quadratic spectral kernel under the asymptotic mean squared error… read more here.

Keywords: kernel; choice har; optimal kernel; kernel choice ... See more keywords
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Empirical kernel map-based multilayer extreme learning machines for representation learning

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recommendations! Published in 2018 at "Neurocomputing"

DOI: 10.1016/j.neucom.2018.05.032

Abstract: Abstract Recently, multilayer extreme learning machine (ML-ELM) and hierarchical extreme learning machine (H-ELM) were developed for representation learning whose training time can be reduced from hours to seconds compared to traditional stacked autoencoder (SAE). However,… read more here.

Keywords: representation learning; kernel; extreme learning; layer ... See more keywords
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Non-reversible guided Metropolis kernel

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recommendations! Published in 2023 at "Journal of Applied Probability"

DOI: 10.1017/jpr.2022.109

Abstract: We construct a class of non-reversible Metropolis kernels as a multivariate extension of the guided-walk kernel proposed by Gustafson (Statist. Comput.8, 1998). The main idea of our method is to introduce a projection that maps… read more here.

Keywords: metropolis kernel; kernel; reversible guided; guided metropolis ... See more keywords
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Efficient Iterative Dynamic Kernel Principal Component Analysis Monitoring Method for the Batch Process with Super-large-scale Data Sets

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recommendations! Published in 2021 at "ACS Omega"

DOI: 10.1021/acsomega.0c06039

Abstract: The Internet environment has provided massive data to the actual industrial production process. It not only has large amounts of data but also has a high data dimension, which brings challenges to the traditional statistical… read more here.

Keywords: kernel; principal component; kernel principal; matrix ... See more keywords
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A classifier for multi-dimensional datasets based on Bayesian multiple kernel grouping learning

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recommendations! Published in 2019 at "Journal of Statistical Computation and Simulation"

DOI: 10.1080/00949655.2019.1612395

Abstract: ABSTRACT This paper proposes an algorithm for the classification of multi-dimensional datasets based on the conjugate Bayesian Multiple Kernel Grouping Learning (BMKGL). Using conjugate Bayesian framework improves the computation efficiency. Multiple kernels instead of a… read more here.

Keywords: datasets based; kernel; dimensional datasets; multiple kernel ... See more keywords