19 search results - page 1 / 4 » Learning from data with uncertain labels by boosting credal ... |
KDD
2009
ACM
14 years 6 months ago
2009
ACM
CVPR
2007
IEEE
15 years 1 months ago
2007
IEEE
We present an integrated framework for learning asymmetric boosted classifiers and online learning to address the problem of online learning asymmetric boosted classifiers, which ...
KDD
2007
ACM
14 years 11 months ago
2007
ACM
Typical approaches to multi-label classification problem require learning an independent classifier for every label from all the examples and features. This can become a computati...
CVPR
2004
IEEE
15 years 1 months ago
2004
IEEE
We consider the problem of the binary classification on imbalanced data, in which nearly all the instances are labelled as one class, while far fewer instances are labelled as the...
ICMLA
2010
13 years 9 months ago
2010
Abstract--Learning multiple related tasks from data simultaneously can improve predictive performance relative to learning these tasks independently. In this paper we propose a nov...