112 search results - page 7 / 23 » Gaussian Processes for Machine Learning (GPML) Toolbox |
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...
ICML
2005
IEEE
14 years 8 months ago
2005
IEEE
When monitoring spatial phenomena, which are often modeled as Gaussian Processes (GPs), choosing sensor locations is a fundamental task. A common strategy is to place sensors at t...
ICML
2004
IEEE
14 years 8 months ago
2004
IEEE
Many real-world classification tasks involve the prediction of multiple, inter-dependent class labels. A prototypical case of this sort deals with prediction of a sequence of labe...
ML
2002
ACM
13 years 7 months ago
2002
ACM
In this paper, we elaborate on the well-known relationship between Gaussian Processes (GP) and Support Vector Machines (SVM) under some convex assumptions for the loss functions. ...