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Multivariate kernel density estimation
Kernel density estimation is a nonparametric technique for density estimation i.e., estimation of probability density functions, which is one of the…
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Related topics
Related topics
12 relations
Bivariate data
C++
Convolution
Cross-validation (statistics)
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Broader (1)
Computational statistics
Papers overview
Semantic Scholar uses AI to extract papers important to this topic.
2017
2017
A Model for Assessing Pedestrian Corridors. Application to Vitoria-Gasteiz City (Spain)
Javier Martinez
,
B. M. Ramos
,
E. Pérez
,
I. O. Pastor
2017
Corpus ID: 45031791
From a mobility perspective, walking is considered to be the most sustainable transport mode. One of the consequences of motor…
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2013
2013
Handling the curse of dimensionality in multivariate kernel density estimation
J. Crabbe
2013
Corpus ID: 132003564
2011
2011
Quasi-continuous maximum entropy distribution approximation with kernel density
Thomas Mazzoni
,
E. Reucher
International Journal of Information and Decision…
2011
Corpus ID: 17687980
This paper extends maximum entropy estimation of discrete probability distributions to the continuous case. This transition leads…
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2011
2011
Multivariate kernel diffusion for surface denoising
Khaled Tarmissi
,
A. Hamza
Signal, Image and Video Processing
2011
Corpus ID: 15489522
In this paper, we introduce a 3D mesh denoising method based on kernel density estimation. The proposed approach is able to…
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2008
2008
Background subtraction based on adaptive non-parametric model
Qin Wan
,
Yaonan Wang
World Congress on Intelligent Control and…
2008
Corpus ID: 14758167
Object detection is an important basis for tracking and recognition in visual surveillance systems via stationary cameras. The…
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2007
2007
Segmentation , 2 D-3 D Registration , and Uncertainty Propagation for Dynamic Roadmapping in Angiographic Interventions
F. Bender
2007
Corpus ID: 10974265
Minimal invasive catheter-guided interventions play an important role in most hospitals all over the world. During the treatment…
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2006
2006
Quick multivariate kernel density estimation for massive data sets
K. Cheng
,
C. Chu
,
D. Lin
2006
Corpus ID: 58905684
Massive data sets are becoming popular in this information era. Due to the limitation of computer memory space and the computing…
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2005
2005
On boosting kernel density methods for multivariate data: density estimation and classification
M. Marzio
,
C. Taylor
Stat. Methods Appl.
2005
Corpus ID: 2110857
Abstract.Statistical learning is emerging as a promising field where a number of algorithms from machine learning are interpreted…
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2001
2001
BIAS REDUCTION AND ELIMINATION WITH KERNEL ESTIMATORS
S. Sain
2001
Corpus ID: 16217921
A great deal of research has focused on improving the bias properties of kernel estimators. One proposal involves removing the…
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1998
1998
Classification via kernel product estimators
Craig A. Cooley
,
S. MacEachern
1998
Corpus ID: 3256631
SUMMARY Multivariate kernel density estimation is often used as the basis for a nonparametric classification technique. However…
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