339 search results - page 35 / 68 » Approximate Inference in Probabilistic Graphical Models with... |
NIPS
2007
14 years 11 months ago
2007
The learning of probabilistic models with many hidden variables and nondecomposable dependencies is an important and challenging problem. In contrast to traditional approaches bas...
ICCV
2007
IEEE
15 years 11 months ago
2007
IEEE
We consider the problem of predicting a sequence of real-valued multivariate states from a given measurement sequence. Its typical application in computer vision is the task of mo...
105
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AAAI
2008
15 years 1 days ago
2008
Research has shown promise in the design of large scale common sense probabilistic models to infer human state from environmental sensor data. These models have made use of mined ...
ICML
2003
IEEE
15 years 10 months ago
2003
IEEE
This paper addresses the problem of classification in situations where the data distribution is not homogeneous: Data instances might come from different locations or times, and t...
108
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JAIR
2010
14 years 8 months ago
2010
Noisy probabilistic relational rules are a promising world model representation for several reasons. They are compact and generalize over world instantiations. They are usually in...