Results 31 to 40 of about 2,482,864 (253)
Kernel regression utilizing heterogeneous datasets
Statistical Theory and Related Fields, 2023 Data analysis in modern scientific research and practice has shifted from analysing a single dataset to coupling several datasets. We propose and study a kernel regression method that can handle the challenge of heterogeneous populations.
Chi-Shian Dai, Jun Shao
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An Improved Model for Kernel Density Estimation Based on Quadtree and Quasi-Interpolation
Mathematics, 2022 There are three main problems for classical kernel density estimation in its application: boundary problem, over-smoothing problem of high (low)-density region and low-efficiency problem of large samples.
Jiecheng Wang, Yantong Liu, Jincai Chang
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FEBS Open Bio, EarlyView.KDAC6 has been associated with cell motility and actin structures, but specific domain contributions are not established. The two catalytic domains have differential effects on motility and F‐actin regulation, affecting cortical F‐actin density, motility, stress fibers, and cell spreading.
Taylor V. Joseph +7 more
wiley +1 more source
Image restoration model for microscopic defocused images based on blurring kernel guidance
HeliyonDefocus blurring imaging seriously affects the observation accuracy and application range of optical microscopes, and the blurring kernel function is a key parameter for high-resolution image restoration.
Yangjie Wei, Qifei Li, Weihan Hou
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A Doubly Smoothed PD Estimator in Credit Risk
Proceedings, 2020 In this work a doubly smoothed probability of default (PD) estimator is proposed based on a smoothed version of the survival Beran’s estimator. The asymptotic properties of both the smoothed survival and PD estimators are proved and their behaviour is ...
Rebeca Peláez Suárez +2 more
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Probability density estimation with tunable kernels using orthogonal forward regression [PDF]
, 2010 A generalized or tunable-kernel model is proposed for probability density function estimation based on an orthogonal forward regression procedure. Each stage of the density estimation process determines a tunable kernel, namely, its center vector and ...
Hong, Xia +3 more
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Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective To clarify the clinical relevance of dopamine transporter single‐photon emission computed tomography (DAT‐SPECT) abnormalities in amyotrophic lateral sclerosis (ALS), with a prespecified focus on sex‐stratified associations with disease progression and short‐term prognosis.
Tomoya Kawazoe +7 more
wiley +1 more source
IET Wireless Sensor SystemsThis paper introduces a kernel‐based approach to enhance the security of distributed estimation in the presence of adversary links. Adversary links often degrade distributed recovery algorithm performance in distributed estimation.
Zahra Khoshkalam +2 more
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Applying the possibilistic C-means algorithm in kernel-induced spaces [PDF]
, 2010 In this paper, we study a kernel extension of the classic possibilistic c-means. In the proposed extension, we implicitly map input patterns into a possibly high-dimensional space by means of positive semidefinite kernels. In this new space, we model the
Masulli, F. +5 more
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Deep Learning Pose Estimation for Phenotyping of Co‐Occurring Hyperkinetic Movement Disorders
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective To explore whether routine outpatient video combined with deep learning‐based pose estimation and clinically interpretable kinematic features can support multi‐label phenotyping of co‐occurring hyperkinetic movement disorders (HMDs).
Laura Cif +17 more
wiley +1 more source