11 search results - page 1 / 3 » Maximum Likelihood in Cost-Sensitive Learning: Model Specifi... |
JMLR
2010
2010
Maximum Likelihood in Cost-Sensitive Learning: Model Specification, Approximations, and Upper Bounds
12 years 11 months ago
The presence of asymmetry in the misclassification costs or class prevalences is a common occurrence in the pattern classification domain. While much interest has been devoted to ...
SODA
2001
ACM
13 years 5 months ago
2001
ACM
Markov networks are a common class of graphical models used in machine learning. Such models use an undirected graph to capture dependency information among random variables in a ...
CVPR
2007
IEEE
14 years 6 months ago
2007
IEEE
Many low-level vision algorithms assume a prior probability over images, and there has been great interest in trying to learn this prior from examples. Since images are very non G...
ICML
2008
IEEE
14 years 5 months ago
2008
IEEE
EM algorithm is a very popular iteration-based method to estimate the parameters of Gaussian Mixture Model from a large observation set. However, in most cases, EM algorithm is no...
CORR
2012
Springer
12 years 2 days ago
2012
Springer
We address the problem of learning the parameters in graphical models when inference is intractable. A common strategy in this case is to replace the partition function with its B...