15 search results - page 2 / 3 » Maximum Margin Learning with Incomplete Data: Learning Netwo... |
ECCV
2008
Springer
14 years 6 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...
UAI
2003
13 years 6 months ago
2003
This paper considers a method that combines ideas from Bayesian learning, Bayesian network inference, and classical hypothesis testing to produce a more reliable and robust test o...
NIPS
2008
13 years 6 months ago
2008
Learning graphical models with hidden variables can offer semantic insights to complex data and lead to salient structured predictors without relying on expensive, sometime unatta...
NIPS
2003
13 years 6 months ago
2003
In typical classification tasks, we seek a function which assigns a label to a single object. Kernel-based approaches, such as support vector machines (SVMs), which maximize the ...
ICMLA
2009
13 years 2 months ago
2009
Exergy is a way to sustainable development and may be defined as the maximum theoretical useful work, while exergy analysis identifies the sources, the magnitude and the causes of...