49 search results - page 3 / 10 » A decision-theoretic generalization of on-line learning and ... |
NIPS
2007
13 years 9 months ago
2007
Semi-supervised inductive learning concerns how to learn a decision rule from a data set containing both labeled and unlabeled data. Several boosting algorithms have been extended...
NIPS
2003
13 years 8 months ago
2003
Learning from ambiguous training data is highly relevant in many applications. We present a new learning algorithm for classification problems where labels are associated with se...
CVPR
2007
IEEE
13 years 11 months ago
2007
IEEE
Detection of objects of a given class is important for many applications. However it is difficult to learn a general detector with high detection rate as well as low false alarm r...
PKDD
2009
Springer
14 years 15 hour ago
2009
Springer
Abstract. This paper focuses on Active Learning with a limited number of queries; in application domains such as Numerical Engineering, the size of the training set might be limite...
PRL
2006
13 years 7 months ago
2006
This paper describes an improved boosting algorithm, the MutualBoost algorithm, and its application in developing a fast and robust Gabor feature based face recognition system. Th...