305 search results - page 3 / 61 » Gene function prediction using labeled and unlabeled data |
BMCBI
2006
13 years 6 months ago
2006
Background: Quantitative simultaneous monitoring of the expression levels of thousands of genes under various experimental conditions is now possible using microarray experiments....
ICCV
2009
IEEE
14 years 11 months ago
2009
IEEE
Random Forests (RFs) have become commonplace
in many computer vision applications. Their
popularity is mainly driven by their high computational
efficiency during both training ...
ICPR
2008
IEEE
14 years 12 days ago
2008
IEEE
We propose a semi-supervised learning algorithm for discriminant analysis, which uses the geometric structure of both labeled and unlabeled samples and perform a manifold regulari...
CVPR
2006
IEEE
14 years 8 months ago
2006
IEEE
We consider the general problem of learning from both labeled and unlabeled data. Given a set of data points, only a few of them are labeled, and the remaining points are unlabele...
NIPS
2004
13 years 7 months ago
2004
In the context of binary classification, we define disagreement as a measure of how often two independently-trained models differ in their classification of unlabeled data. We exp...