59 search results - page 1 / 12 » Most likely heteroscedastic Gaussian process regression |
ICML
2007
IEEE
14 years 11 months ago
2007
IEEE
This paper presents a novel Gaussian process (GP) approach to regression with inputdependent noise rates. We follow Goldberg et al.'s approach and model the noise variance us...
ICML
2005
IEEE
14 years 11 months ago
2005
IEEE
This paper presents an algorithm to estimate simultaneously both mean and variance of a non parametric regression problem. The key point is that we are able to estimate variance l...
ICRA
2010
IEEE
13 years 8 months ago
2010
IEEE
This paper presents a novel approach to data fusion for stochastic processes that model spatial data. It addresses the problem of data fusion in the context of large scale terrain ...
ESANN
2003
2003
Approximately unbiased estimation of conditional variance in heteroscedastic kernel ridge regression
14 years 9 days ago
In this paper we extend a form of kernel ridge regression for data characterised by a heteroscedastic noise process (introduced in Foxall et al. [1]) in order to provide approxima...
ICB
2009
Springer
14 years 5 months ago
2009
Springer
Linear discriminant analysis (LDA) is a popular method in pattern recognition and is equivalent to Bayesian method when the sample distributions of different classes are obey to t...