Variable kernel density estimation

Known as: Variable bandwidth kernel density estimation, Variable kernel density estimator, Adaptive kernel density estimation 
In statistics, adaptive or "variable-bandwidth" kernel density estimation is a form of kernel density estimation in which the size of the kernels… (More)
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Papers overview

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2018
2018
Variable kernel density estimation allows the approximation of a probability density by the mean of differently stretched and… (More)
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Highly Cited
2017
Highly Cited
2017
Estimating the joint probability density function of a dataset is a central task in many machine learning applications. In this… (More)
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2014
2014
Standard fixed symmetric kernel type density estimators are known to encounter problems for positive random variables with a… (More)
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2011
2011
In the main paper we presented results regarding the MSE of CAKE like estimators, and a risk bound for CAKE. In this… (More)
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2009
2009
Many regression schemes deliver a point estimate only, but often it is useful or even essential to quantify the uncertainty… (More)
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2007
2007
Adaptive kernel estimation for unit interval compact bounded densities using beta kernel is considered. Beta kernel is an… (More)
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2005
2005
In recent years, kernel density estimation has been exploited by computer scientists to model several important problems in… (More)
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Highly Cited
2004
Highly Cited
2004
Background modeling is an important component of many vision systems. Existing work in the area has mostly addressed scenes that… (More)
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1994
1994
This paper describes the Stata module akdensity. akdensity extends the official Stata command kdensity that estimates density… (More)
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Highly Cited
1994
Highly Cited
1994
The problem of optimal adaptive estimation of a function at a given point from noisy data is considered. Two procedures are… (More)
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