417 search results - page 21 / 84 » Bayesian inference in estimation of distribution algorithms |
JMLR
2010
13 years 2 months ago
2010
A continuous time Bayesian network (CTBN) uses a structured representation to describe a dynamic system with a finite number of states which evolves in continuous time. Exact infe...
JMLR
2006
13 years 7 months ago
2006
We study the computational and sample complexity of parameter and structure learning in graphical models. Our main result shows that the class of factor graphs with bounded degree...
CVPR
2009
IEEE
15 years 3 months ago
2009
IEEE
Many computer vision problems can be formulated in
a Bayesian framework with Markov Random Field (MRF)
or Conditional Random Field (CRF) priors. Usually, the
model assumes that ...
KI
2009
Springer
14 years 2 months ago
2009
Springer
This paper presents a sequential state estimation method with arbitrary probabilistic models expressing the system’s belief. Probabilistic models can be estimated by Maximum a po...
ICASSP
2011
IEEE
12 years 11 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...