Results 11 to 20 of about 155,817 (215)
Block-encoding dense and full-rank kernels using hierarchical matrices: applications in quantum numerical linear algebra [PDF]
Quantum, 2022 Many quantum algorithms for numerical linear algebra assume black-box access to a block-encoding of the matrix of interest, which is a strong assumption when the matrix is not sparse.
Quynh T. Nguyen +2 more
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Frontiers in Pharmacology, 2023 The target of the study is to predict the inhibitory effect of amide derivatives on xanthine oxidase (XO) by building several models, which are based on the theory of the quantitative structure–activity relationship (QSAR).
Xiaoda Yang +3 more
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Study on radar echo image quality control based on improved convolution technology
暴雨灾害, 2022 Based on the principle of convolution calculation,this study improves the conventional convolution method and constructs the isolated point convolution kernel,linear convolution kernel,and weak echo convolution kernel. Based on this improved conventional
Daoyang NIE, An XIAO, Houjie XIA
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Henderson's method approach to Kernel prediction in partially linear mixed models
Cumhuriyet Science Journal, 2020 In this article, we propose Kernel prediction in partially linear mixed models by using Henderson's method approach. We derive the Kernel estimator and the Kernel predictor via the mixed model equations (MMEs) of Henderson's that they give the best ...
Seçil Yalaz, Özge Kuran
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The Spectral Analysis and Application of Low-degree Modified Spheroidal Hotine Kernel [PDF]
Journal of Geodesy and Geoinformation Science, 2020 The traditional spheroidal kernel results in the spectrum leakage, and the utilization rate of the removed degrees of the measured data is low. Hence, a kind of spheroidal kernel whose high- and low-degrees are both modified is introduced in this ...
MA Jian,WEI Ziqing,REN Hongfei
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A Comparative Analysis of Kernel Subspace Target Detectors for Hyperspectral Imagery
EURASIP Journal on Advances in Signal Processing, 2007 Several linear and nonlinear detection algorithms that are based on spectral matched (subspace) filters are compared. Nonlinear (kernel) versions of these spectral matched detectors are also given and their performance is compared with linear versions ...
Nasser M. Nasrabadi, Heesung Kwon
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Universal Local Linear Kernel Estimators in Nonparametric Regression
Mathematics, 2022 New local linear estimators are proposed for a wide class of nonparametric regression models. The estimators are uniformly consistent regardless of satisfying traditional conditions of dependence of design elements.
Yuliana Linke +5 more
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Revista Tecnológica, 2017 El objetivo del trabajo fue evaluar la eficiencia del clasificador Máquina de Soporte Vectorial (SVM) con el método de separación linear, cuando se utiliza el algoritmo de extracción de características Histograma Orientado a Gradientes (HOG) y cuando no ...
Jessica Johanna Morales Carrillo
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A Linear Kernel for Planar Total Dominating Set [PDF]
Discrete Mathematics & Theoretical Computer Science, 2018 A total dominating set of a graph $G=(V,E)$ is a subset $D \subseteq V$ such that every vertex in $V$ is adjacent to some vertex in $D$. Finding a total dominating set of minimum size is NP-hard on planar graphs and W[2]-complete on general graphs when ...
Valentin Garnero, Ignasi Sau
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Journal of Numerical Analysis and Approximation Theory, 2023 Our aim in this work is to extend the primal-dual interior point method based on a kernel function for linear fractional problem. We apply the techniques of kernel function-based interior point methods to solve a standard linear fractional program.
Mousaab Bouafia, Adnan Yassine
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