922 search results - page 1 / 185 » Learning Gaussian Process Models from Uncertain Data |
ICONIP
2009
13 years 2 months ago
2009
It is generally assumed in the traditional formulation of supervised learning that only the outputs data are uncertain. However, this assumption might be too strong for some learni...
ICANN
2011
Springer
12 years 8 months ago
2011
Springer
Abstract. In many supervised learning tasks it can be costly or infeasible to obtain objective, reliable labels. We may, however, be able to obtain a large number of subjective, po...
JAIR
1998
13 years 4 months ago
1998
This paper presents a general and efficient framework for probabilistic inference and learning from arbitrary uncertain information. It exploits the calculation properties of fini...
ICML
2007
IEEE
14 years 5 months ago
2007
IEEE
Markov decision processes are an effective tool in modeling decision-making in uncertain dynamic environments. Since the parameters of these models are typically estimated from da...
ICML
2007
IEEE
14 years 5 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 ...