922 search results - page 58 / 185 » Learning Gaussian Process Models from Uncertain Data |
ICML
2010
IEEE
13 years 9 months ago
2010
IEEE
The hierarchical Dirichlet process (HDP) is a Bayesian nonparametric mixed membership model--each data point is modeled with a collection of components of different proportions. T...
CORR
2012
Springer
12 years 4 months ago
2012
Springer
Determinantal point processes (DPPs), which arise in random matrix theory and quantum physics, are natural models for subset selection problems where diversity is preferred. Among...
ECAI
2006
Springer
14 years 5 days ago
2006
Springer
Abstract. We formulate the problem of least squares temporal difference learning (LSTD) in the framework of least squares SVM (LS-SVM). To cope with the large amount (and possible ...
IPMI
2011
Springer
12 years 12 months ago
2011
Springer
In this paper we construct an atlas that captures functional characteristics of a cognitive process from a population of individuals. The functional connectivity is encoded in a lo...
JMLR
2002
13 years 8 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...