1900 search results - page 6 / 380 » Gaussian Processes for Machine Learning |
ICML
2010
IEEE
13 years 8 months ago
2010
IEEE
This paper proposes a multiple instance learning (MIL) algorithm for Gaussian processes (GP). The GP-MIL model inherits two crucial benefits from GP: (i) a principle manner of lea...
ESSMAC
2003
Springer
14 years 24 days ago
2003
Springer
Kernel-based non-parametric models have been applied widely over recent years. However, the associated computational complexity imposes limitations on the applicability of those me...
ICML
2008
IEEE
14 years 8 months ago
2008
IEEE
Stationarity is often an unrealistic prior assumption for Gaussian process regression. One solution is to predefine an explicit nonstationary covariance function, but such covaria...
ICML
2010
IEEE
13 years 8 months ago
2010
IEEE
We combine Bayesian online change point detection with Gaussian processes to create a nonparametric time series model which can handle change points. The model can be used to loca...
ICML
2007
IEEE
14 years 8 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...