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IJCNN
2008
IEEE
13 years 11 months ago
Sparse kernel density estimator using orthogonal regression based on D-Optimality experimental design
— A novel sparse kernel density estimator is derived based on a regression approach, which selects a very small subset of significant kernels by means of the D-optimality experi...
Sheng Chen, Xia Hong, Chris J. Harris
SIAMCO
2008
98views more  SIAMCO 2008»
13 years 4 months ago
Kernel Density Estimation and Goodness-of-Fit Test in Adaptive Tracking
We investigate the asymptotic properties of a recursive kernel density estimator associated with the driven noise of a linear regression in adaptive tracking. We provide an almost ...
Bernard Bercu, Bruno Portier
PRL
2002
106views more  PRL 2002»
13 years 4 months ago
Kernel density estimation with adaptive varying window size
A new method of kernel density estimation with a varying adaptive window size is proposed. It is based on the socalled intersection of confidence intervals (ICI) rule. Several exa...
Vladimir Katkovnik, Ilya Shmulevich
ICASSP
2011
IEEE
12 years 8 months ago
Automatic audio tag classification via semi-supervised canonical density estimation
We propose a novel semi-supervised method for building a statistical model that represents the relationship between sounds and text labels (“tags”). The proposed method, named...
Jun Takagi, Yasunori Ohishi, Akisato Kimura, Masas...
CVPR
2012
IEEE
11 years 7 months ago
Background modeling using adaptive pixelwise kernel variances in a hybrid feature space
Recent work on background subtraction has shown developments on two major fronts. In one, there has been increasing sophistication of probabilistic models, from mixtures of Gaussi...
Manjunath Narayana, Allen R. Hanson, Erik G. Learn...