124 search results - page 15 / 25 » Learning from Positive and Unlabeled Examples with Different... |
KDD
2008
ACM
14 years 7 months ago
2008
ACM
The effectiveness of knowledge transfer using classification algorithms depends on the difference between the distribution that generates the training examples and the one from wh...
ICDE
2008
IEEE
14 years 8 months ago
2008
IEEE
Abstract-- Many applications are driven by evolving data -patterns in web traffic, program execution traces, network event logs, etc., are often non-stationary. Building prediction...
KDD
2009
ACM
14 years 8 months ago
2009
ACM
One common predictive modeling challenge occurs in text mining problems is that the training data and the operational (testing) data are drawn from different underlying distributi...
ICCV
2007
IEEE
14 years 9 months ago
2007
IEEE
Many recognition algorithms depend on careful positioning of an object into a canonical pose, so the position of features relative to a fixed coordinate system can be examined. Cu...
SDM
2008
SIAM
13 years 8 months ago
2008
SIAM
Covariate shift is a situation in supervised learning where training and test inputs follow different distributions even though the functional relation remains unchanged. A common...