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Kernel density estimation

Known as: Kernel density estimate, Kernel density, Parzen Windows 
In statistics, kernel density estimation (KDE) is a non-parametric way to estimate the probability density function of a random variable. Kernel… 
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AnalyticaApache SparkC++Cluster analysis

Broader (1)

Machine learning

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2013
Highly Cited
2013
Determination of Formation Organic Carbon Content Using a New Neutron-Induced Gamma Ray Spectroscopy Service that Directly Measures Carbon
Over the past few decades, many techniques have been developed for the log e valuation of organic-rich rocks (ORR). More recently… 
2006
2006
MAI-Free MC-CDMA Systems Based on Hadamard–Walsh Codes
It is known that multicarrier code-division multiple-access (MC-CDMA) systems suffer from multiaccess interference (MAI) when the… 
2005
2005
ABODE: Kernel home range estimation for ArcGIS, using VBA and ArcObjects
K Ke er rn ne el l H Ho om me e R Ra an ng ge e E Es st ti im ma at ti io on n f fo or r A Ar rc cG GI IS S, , u us si in ng g V… 
2004
2004
A Kernel-Based Semi-Naïve Bayesian Classifier Using P-Trees
A novel semi-naive Bayesian classifier is introduced that is particularly suitable to data with many attributes. The naive… 
2003
2003
Non-Linear Variance Reduction Techniques in Biometric Authentication
In this paper, several approaches that can be used to improve biometric authentication applications are proposed. The idea is… 
1998
1998
Facial Memory Is Kernel Density Estimation (Almost)
We compare the ability of three exemplar-based memory models, each using three different face stimulus representations, to… 
1998
1998
Pose estimation in SAR using an information theoretic criterion
In this paper we formulate pose estimation statistically and show that pose can be estimated from a low dimensional feature space… 
1995
1995
Identification of cubic systems using higher order moments of i.i.d. signals
A simple method for estimating the Volterra kernels of cubic systems with a zero-mean i.i.d. input is presented. This method… 
1989
1989
On parametric density estimation
SUMMARY The paper makes a critical assessment of Aitchison's criterion of density estimation. It seems not to satisfy certain… 
1989
1989
Prony, Pisarenko, and the matrix pencil: a unified presentation
In the past, the Prony and Pisarenko algorithms have been widely used in the pole zero identification of linear systems as well… 
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