129 search results - page 8 / 26 » Active learning with extremely sparse labeled examples |
ICDM
2009
IEEE
14 years 2 months ago
2009
IEEE
—Active learning can actively select or construct examples to label to reduce the number of labeled examples needed for building accurate classifiers. However, previous works of...
CIVR
2006
Springer
13 years 11 months ago
2006
Springer
Abstract. Interactively learning from a small sample of unlabeled examples is an enormously challenging task. Relevance feedback and more recently active learning are two standard ...
IJCAI
2003
13 years 9 months ago
2003
Multi-view learners reduce the need for labeled data by exploiting disjoint sub-sets of features (views), each of which is sufficient for learning. Such algorithms assume that eac...
SDM
2004
SIAM
13 years 9 months ago
2004
SIAM
Most previously proposed mining methods on data streams make an unrealistic assumption that "labelled" data stream is readily available and can be mined at anytime. Howe...
CEC
2010
IEEE
13 years 5 months ago
2010
IEEE
The great majority of genetic programming (GP) algorithms that deal with the classification problem follow a supervised approach, i.e., they consider that all fitness cases availab...