161 search results - page 14 / 33 » A Multiple Resampling Method for Learning from Imbalanced Da... |
CVPR
2009
IEEE
15 years 2 months ago
2009
IEEE
The computer aided diagnosis (CAD) problems of detecting
potentially diseased structures from medical images are
typically distinguished by the following challenging characterist...
JMLR
2006
13 years 7 months ago
2006
While classical kernel-based learning algorithms are based on a single kernel, in practice it is often desirable to use multiple kernels. Lanckriet et al. (2004) considered conic ...
KDD
2005
ACM
14 years 1 months ago
2005
ACM
Data clustering represents an important tool in exploratory data analysis. The lack of objective criteria render model selection as well as the identification of robust solutions...
KDD
2008
ACM
14 years 8 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...
ECCV
2010
Springer
13 years 7 months ago
2010
Springer
Abstract. Multiple-instance learning (MIL) allows for training classifiers from ambiguously labeled data. In computer vision, this learning paradigm has been recently used in many ...