45 search results - page 4 / 9 » Using the Equivalent Kernel to Understand Gaussian Process R... |
ICCV
2009
IEEE
13 years 5 months ago
2009
IEEE
Poisson regression models the noisy output of a counting function as a Poisson random variable, with a log-mean parameter that is a linear function of the input vector. In this wo...
CVPR
2010
IEEE
13 years 7 months ago
2010
IEEE
Kernel regression techniques such as Relevance Vector Machine (RVM) regression, Support Vector Regression and Gaussian processes are widely used for solving many computer vision p...
ACCV
2010
Springer
13 years 2 months ago
2010
Springer
Detecting instances of unknown categories is an important task for a multitude of problems such as object recognition, event detection, and defect localization. This paper investig...
ESANN
2007
13 years 9 months ago
2007
Abstract. From the echoes of their vocalisations bats extract information about the positions of reflectors. To gain an understanding of how target position is translated into neu...
ESANN
2003
2003
Approximately unbiased estimation of conditional variance in heteroscedastic kernel ridge regression
13 years 9 months 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...