69 search results - page 11 / 14 » Random Sampling of Labeled Tournaments |
RECOMB
2006
Springer
14 years 9 months ago
2006
Springer
Permutation of class labels is a common approach to build null distributions for significance analyis of microarray data. It is assumed to produce random score distributions, which...
ICML
2007
IEEE
14 years 9 months ago
2007
IEEE
We present a new machine learning framework called "self-taught learning" for using unlabeled data in supervised classification tasks. We do not assume that the unlabele...
CVPR
2010
IEEE
14 years 5 months ago
2010
IEEE
Hierarchical conditional random fields have been successfully applied to object segmentation. One reason is their ability to incorporate contextual information at different scales....
TCS
2011
13 years 3 months ago
2011
The PAC-learning model is distribution-independent in the sense that the learner must reach a learning goal with a limited number of labeled random examples without any prior know...
MICCAI
2010
Springer
13 years 7 months ago
2010
Springer
Abstract. Learning-based approaches have become increasingly practical in medical imaging. For a supervised learning strategy, the quality of the trained algorithm (usually a class...