405 search results - page 23 / 81 » Bayesian Gaussian Process Latent Variable Model |
JCST
2010
14 years 8 months ago
2010
In the Bayesian mixture modeling framework it is possible to infer the necessary number of components to model the data and therefore it is unnecessary to explicitly restrict the n...
GRC
2010
IEEE
14 years 10 months ago
2010
IEEE
Inference of latent variables from complicated data is one important problem in data mining. The high dimensionality and high complexity of real world data often make accurate infe...
ICIP
2003
IEEE
15 years 11 months ago
2003
IEEE
Background subtraction is an essential processing component for many video applications. However, its development has largely been application driven and done in ad hoc manners. I...
NIPS
2000
14 years 10 months ago
2000
We develop an approach for a sparse representation for Gaussian Process (GP) models in order to overcome the limitations of GPs caused by large data sets. The method is based on a...
ICML
2003
IEEE
15 years 10 months ago
2003
IEEE
We present a novel Bayesian approach to the problem of value function estimation in continuous state spaces. We define a probabilistic generative model for the value function by i...