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Density estimation by entropy maximization with kernels

2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2015
The estimation of a probability density function is one of the most fundamental problems in statistics. The goal is achieving a desirable balance between flexibility while maintaining as simple a form as possible to allow for generalization, and efficient implementation.
Gengshen Fu   +2 more
openaire   +1 more source

Kernel Density Estimation

1991
The idea of kernel estimators was introduced by Rosenblatt (1956). In Chapter 1 needles were used in the observations as a very noisy method to approximate density.
openaire   +1 more source

Kernel density estimation: the general case

Statistics & Probability Letters, 2001
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Campos, V. S. M., Dorea, C. C. Y.
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TAKDE: Temporal Adaptive Kernel Density Estimator for Real-Time Dynamic Density Estimation

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023
Yinsong Wang   +2 more
exaly  

Fast feature selection for interval-valued data through kernel density estimation entropy

International Journal of Machine Learning and Cybernetics, 2020
Jianhua Dai   +2 more
exaly  

Anomaly Detection Using Local Kernel Density Estimation and Context-Based Regression

IEEE Transactions on Knowledge and Data Engineering, 2020
Weiming Hu, Bing Li, Ou Wu
exaly  

Tessellation-based Kernel Density Estimation

2021 4th International Conference on Algorithms, Computing and Artificial Intelligence, 2021
Vladislav Belov, Radek Marik
openaire   +1 more source

A tutorial on kernel density estimation and recent advances

Biostatistics and Epidemiology, 2017
Yen-Chi Chen
exaly  

A kernel density estimation method for networks, its computational method and a GIS‐based tool

International Journal of Geographical Information Science, 2009
Kokichi Sugihara
exaly  

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