454 search results - page 41 / 91 » Bayesian learning of measurement and structural models |
ICONIP
2007
13 years 10 months ago
2007
Variational methods for approximate inference in machine learning often adapt a parametric probability distribution to optimize a given objective function. This view is especially ...
JMLR
2010
13 years 3 months ago
2010
Variational Bayesian (VB) methods are typically only applied to models in the conjugate-exponential family using the variational Bayesian expectation maximisation (VB EM) algorith...
ICCV
2003
IEEE
14 years 11 months ago
2003
IEEE
In this paper, we formulate the shape localization problem in the Bayesian framework. In the learning stage, we propose the Constrained RankBoost approach to model the likelihood ...
GECCO
2004
Springer
14 years 2 months ago
2004
Springer
This paper describes a continuous estimation of distribution algorithm (EDA) to solve decomposable, real-valued optimization problems quickly, accurately, and reliably. This is the...
KES
2007
Springer
14 years 3 months ago
2007
Springer
Bayesian Networks are proven to be a comprehensive model to describe causal relationships among domain attributes with probabilistic measure of conditional dependency. However, dep...