151 search results - page 8 / 31 » Learning on the border: active learning in imbalanced data c... |
ICCV
2009
IEEE
13 years 5 months ago
2009
IEEE
Multi-label learning is useful in visual object recognition when several objects are present in an image. Conventional approaches implement multi-label learning as a set of binary...
CIKM
2008
Springer
13 years 9 months ago
2008
Springer
Proactive learning is a generalization of active learning designed to relax unrealistic assumptions and thereby reach practical applications. Active learning seeks to select the m...
ICML
2002
IEEE
14 years 8 months ago
2002
IEEE
In a multi-view problem, the features of the domain can be partitioned into disjoint subsets (views) that are sufficient to learn the target concept. Semi-supervised, multi-view a...
LREC
2010
13 years 9 months ago
2010
In the paper we investigate the impact of data size on a Word Sense Disambiguation task (WSD). We question the assumption that the knowledge acquisition bottleneck, which is known...
JIFS
2008
13 years 7 months ago
2008
The crucial issue in many classification applications is how to achieve the best possible classifier with a limited number of labeled data for training. Training data selection is ...