118 search results - page 15 / 24 » Hierarchic Bayesian models for kernel learning |
TMI
2010
13 years 6 months ago
2010
Abstract—We propose a probabilistic model for analyzing spatial activation patterns in multiple functional magnetic resonance imaging (fMRI) activation images such as repeated ob...
ACL
2010
13 years 6 months ago
2010
This paper establishes a connection between two apparently very different kinds of probabilistic models. Latent Dirichlet Allocation (LDA) models are used as "topic models&qu...
ICML
2005
IEEE
14 years 8 months ago
2005
IEEE
The Relevance Vector Machine (RVM) is a sparse approximate Bayesian kernel method. It provides full predictive distributions for test cases. However, the predictive uncertainties ...
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...
GECCO
2006
Springer
13 years 11 months ago
2006
Springer
This paper describes and analyzes sporadic model building, which can be used to enhance the efficiency of the hierarchical Bayesian optimization algorithm (hBOA) and other advance...