750 search results - page 90 / 150 » Learning SVMs from Sloppily Labeled Data |
FGR
2008
IEEE
14 years 3 months ago
2008
IEEE
Many facial image analysis methods rely on learningbased techniques such as Adaboost or SVMs to project classifiers based on the selection of local image filters (e.g., Haar and...
MICCAI
2005
Springer
14 years 10 months ago
2005
Springer
Abstract. In this paper, we propose a new dynamic learning framework that requires a small amount of labeled data in the beginning, then incrementally discovers informative unlabel...
CIKM
2008
Springer
13 years 11 months ago
2008
Springer
In this work we try to bridge the gap often encountered by researchers who find themselves with few or no labeled examples from their desired target domain, yet still have access ...
CVPR
2007
IEEE
14 years 11 months ago
2007
IEEE
A good distance metric is crucial for unsupervised learning from high-dimensional data. To learn a metric without any constraint or class label information, most unsupervised metr...
CVPR
2005
IEEE
14 years 11 months ago
2005
IEEE
Training datasets for learning of object categories are often contaminated or imperfect. We explore an approach to automatically identify examples that are noisy or troublesome fo...