265 search results - page 31 / 53 » A Scheme for Approximating Probabilistic Inference |
ICML
2008
IEEE
14 years 9 months ago
2008
IEEE
Deep Belief Networks (DBN's) are generative models that contain many layers of hidden variables. Efficient greedy algorithms for learning and approximate inference have allow...
CVPR
2009
IEEE
15 years 3 months ago
2009
IEEE
Image classification and annotation are important problems
in computer vision, but rarely considered together. Intuitively,
annotations provide evidence for the class label,
and...
ICDE
2007
IEEE
14 years 10 months ago
2007
IEEE
The ability to store and query uncertain information is of great benefit to databases that infer values from a set of observations, including databases of moving objects, sensor r...
ICCD
2002
IEEE
14 years 5 months ago
2002
IEEE
We represent switching activity in VLSI circuits using a graphical probabilistic model based on Cascaded Bayesian Networks (CBN’s). We develop an elegant method for maintaining ...
NN
1997
Springer
14 years 28 days 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...