824 search results - page 83 / 165 » Learning probabilistic logic models from probabilistic examp... |
153
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ECCV
2008
Springer
16 years 5 months ago
2008
Springer
Probabilistic graphical models such as Bayesian Networks have been increasingly applied to many computer vision problems. Accuracy of inferences in such models depends on the quali...
170
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ESOP
2011
Springer
14 years 7 months ago
2011
Springer
Abstract. The Bayesian approach to machine learning amounts to inferring posterior distributions of random variables from a probabilistic model of how the variables are related (th...
146
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CVPR
2003
IEEE
16 years 6 months ago
2003
IEEE
This paper addresses the problem of capturing the dynamics for exemplar-based recognition systems. Traditional HMM provides a probabilistic tool to capture system dynamics and in ...
154
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CEC
2009
IEEE
15 years 10 months ago
2009
IEEE
—Structure learning is a crucial component of a multivariate Estimation of Distribution algorithm. It is the part which determines the interactions between variables in the proba...
187
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TSE
2011
14 years 11 months ago
2011
— We propose a new probabilistic temporal logic iLTL which captures properties of systems whose state can be represented by probability mass functions (pmf’s). Using iLTL, we c...