132 search results - page 5 / 27 » Context-specific approximation in probabilistic inference |
NIPS
2008
13 years 8 months ago
2008
Hierarchical probabilistic modeling of discrete data has emerged as a powerful tool for text analysis. Posterior inference in such models is intractable, and practitioners rely on...
IPSN
2004
Springer
14 years 24 days ago
2004
Springer
We present a methodology for a sensor network to answer queries with limited and stochastic information using probabilistic techniques. This capability is useful in that it allows...
ICML
2004
IEEE
14 years 8 months ago
2004
IEEE
Variational inference methods, including mean field methods and loopy belief propagation, have been widely used for approximate probabilistic inference in graphical models. While ...
ICML
2004
IEEE
14 years 8 months ago
2004
IEEE
A standard method for approximating averages in probabilistic models is to construct a Markov chain in the product space of the random variables with the desired equilibrium distr...
NIPS
1998
13 years 8 months ago
1998
Inference is a key component in learning probabilistic models from partially observable data. When learning temporal models, each of the many inference phases requires a complete ...