157 search results - page 9 / 32 » On Bayesian bounds |
UAI
2003
14 years 12 months ago
2003
We prove that perfect distributions exist when using a finite number of bits to represent the parameters of a Bayesian network. In addition, we provide an upper bound on the prob...
JAIR
2007
14 years 10 months ago
2007
The paper presents a new sampling methodology for Bayesian networks that samples only a subset of variables and applies exact inference to the rest. Cutset sampling is a network s...
JMLR
2010
14 years 5 months ago
2010
We introduce a variational inference framework for training the Gaussian process latent variable model and thus performing Bayesian nonlinear dimensionality reduction. This method...
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SUM
2009
Springer
15 years 5 months ago
2009
Springer
Bayesian networks are probabilistic graphical models widely employed in AI for the implementation of knowledge-based systems. Standard inference algorithms can update the beliefs a...
NN
1997
Springer
15 years 2 months ago
1997
Springer
Bayesian networks are directed acyclic graphs that represent dependencies between variables in a probabilistic model. Many time series models, including the hidden Markov models (H...