112 search results - page 3 / 23 » Gaussian Processes for Machine Learning (GPML) Toolbox |
JMLR
2002
13 years 5 months ago
2002
Approximate Bayesian Gaussian process (GP) classification techniques are powerful nonparametric learning methods, similar in appearance and performance to support vector machines....
ECML
2006
Springer
13 years 9 months ago
2006
Springer
Abstract. In contrast to the standard inductive inference setting of predictive machine learning, in real world learning problems often the test instances are already available at ...
ICML
2009
IEEE
14 years 7 months ago
2009
IEEE
We propose an analytic moment-based filter for nonlinear stochastic dynamic systems modeled by Gaussian processes. Exact expressions for the expected value and the covariance matr...
ICML
2007
IEEE
14 years 7 months ago
2007
IEEE
Supervised learning is difficult with high dimensional input spaces and very small training sets, but accurate classification may be possible if the data lie on a low-dimensional ...
ICML
2008
IEEE
14 years 7 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...