1900 search results - page 4 / 380 » Gaussian Processes for Machine Learning |
ICML
2007
IEEE
14 years 8 months ago
2007
IEEE
The Gaussian process latent variable model (GP-LVM) is a powerful approach for probabilistic modelling of high dimensional data through dimensional reduction. In this paper we ext...
ICML
2005
IEEE
14 years 8 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...
ICML
2008
IEEE
14 years 8 months ago
2008
IEEE
Point processes are difficult to analyze because they provide only a sparse and noisy observation of the intensity function driving the process. Gaussian Processes offer an attrac...
ESSMAC
2003
Springer
14 years 24 days ago
2003
Springer
Abstract. Gaussian process models provide a probabilistic non-parametric modelling approach for black-box identification of nonlinear dynamic systems. The Gaussian processes can h...
ICML
2005
IEEE
14 years 8 months ago
2005
IEEE
In this paper, we propose a probabilistic kernel approach to preference learning based on Gaussian processes. A new likelihood function is proposed to capture the preference relat...