256 search results - page 31 / 52 » Uncertainties in Bayesian Geometric Models |
103
Voted
ICASSP
2011
IEEE
14 years 4 months ago
2011
IEEE
The Dirichlet Process Mixture (DPM) models represent an attractive approach to modeling latent distributions parametrically. In DPM models the Dirichlet process (DP) is applied es...
111
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NIPS
2004
15 years 1 months ago
2004
In this paper we propose a probabilistic model for online document clustering. We use non-parametric Dirichlet process prior to model the growing number of clusters, and use a pri...
123
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ESSMAC
2003
Springer
15 years 5 months ago
2003
Springer
Gaussian Process prior models, as used in Bayesian non-parametric statistical models methodology are applied to implement a nonlinear adaptive control law. The expected value of a...
111
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TCSV
2008
15 years 11 days ago
2008
This paper describes a probabilistic framework for faithful reproduction of dynamic facial expressions on a synthetic face model with MPEG-4 facial animation parameters (FAPs) whil...
ECIR
2009
Springer
15 years 9 months ago
2009
Springer
Probabilistic retrieval models usually rank documents based on a scalar quantity. However, such models lack any estimate for the uncertainty associated with a document’s rank. Fu...