175 search results - page 13 / 35 » Parameter space exploration with Gaussian process trees |
ICASSP
2011
IEEE
12 years 11 months ago
2011
IEEE
In supervector UBM/GMM paradigm, each acoustic file is represented by the mean parameters of a GMM model. This supervector space is used as a data representation space, which has...
CIARP
2009
Springer
14 years 2 months ago
2009
Springer
When we look at images taken from outdoor scenes, much of the information perceived is due to the ligthing conditions. In these scenes, the solar beams interact with the atmosphere...
JMLR
2002
13 years 7 months ago
2002
A central problem in learning is selection of an appropriate model. This is typically done by estimating the unknown generalization errors of a set of models to be selected from a...
IROS
2007
IEEE
14 years 1 months ago
2007
IEEE
— In this paper, we present an approach that applies the reinforcement learning principle to the problem of learning height control policies for aerial blimps. In contrast to pre...
ICASSP
2011
IEEE
12 years 11 months ago
2011
IEEE
One of central topics of kernel machines in the field of machine learning is a model selection, especially a selection of a kernel or its parameters. In our previous work, we dis...