10 search results - page 2 / 2 » Probability Density Estimation With Tunable Kernels Using Or... |
ICIC
2007
Springer
13 years 11 months ago
2007
Springer
Abstract. Using the classical Parzen window (PW) estimate as the target function, the sparse kernel density estimator is constructed in a forward constrained regression manner. The...
ACML
2009
Springer
13 years 12 months ago
2009
Springer
Many regression schemes deliver a point estimate only, but often it is useful or even essential to quantify the uncertainty inherent in a prediction. If a conditional density estim...
ECCV
2002
Springer
14 years 7 months ago
2002
Springer
Abstract. Two new techniques based on nonparametric estimation of probability densities are introduced which improve on the performance of equivalent robust methods currently emplo...
CSDA
2008
13 years 5 months ago
2008
An m-sample semiparametric model in which the ratio of m - 1 probability density functions with respect to the mth is of a known parametric form without reference to any parametri...
NECO
2011
13 years 8 days ago
2011
Selection of an optimal estimator typically relies on either supervised training samples (pairs of measurements and their associated true values), or a prior probability model for...