26 search results - page 4 / 6 » Restricted Decontamination for the Imbalanced Training Sampl... |
CVPR
2010
IEEE
13 years 3 months ago
2010
IEEE
This paper shows that the performance of a binary classifier can be significantly improved by the processing of structured unlabeled data, i.e. data are structured if knowing the ...
JAIR
2000
13 years 5 months ago
2000
A major problem in machine learning is that of inductive bias: how to choose a learner's hypothesis space so that it is large enough to contain a solution to the problem bein...
PAMI
2006
13 years 5 months ago
2006
Multiple-instance problems arise from the situations where training class labels are attached to sets of samples (named bags), instead of individual samples within each bag (called...
CVPR
2003
IEEE
14 years 7 months ago
2003
IEEE
Inhomogeneous Gibbs model (IGM) [4] is an effective maximum entropy model in characterizing complex highdimensional distributions. However, its training process is so slow that th...
AMFG
2003
IEEE
13 years 10 months ago
2003
IEEE
Recognition under illumination variations is a challenging problem. The key is to successfully separate the illumination source from the observed appearance. Once separated, what ...