243 search results - page 20 / 49 » Learning Classifiers from Distributed, Ontology-Extended Dat... |
PKDD
2010
Springer
13 years 5 months ago
2010
Springer
We consider the problem of numerical stability and model density growth when training a sparse linear model from massive data. We focus on scalable algorithms that optimize certain...
EMNLP
2006
13 years 9 months ago
2006
Discriminative learning methods are widely used in natural language processing. These methods work best when their training and test data are drawn from the same distribution. For...
DMIN
2007
13 years 9 months ago
2007
- The classifier built from a data set with a highly skewed class distribution generally predicts the more frequently occurring classes much more often than the infrequently occurr...
ICCV
2005
IEEE
14 years 9 months ago
2005
IEEE
In this paper, a new learning framework?probabilistic boosting-tree (PBT), is proposed for learning two-class and multi-class discriminative models. In the learning stage, the pro...
PAMI
2008
13 years 7 months ago
2008
We address the issue of classifying complex data. We focus on three main sources of complexity, namely, the high dimensionality of the observed data, the dependencies between these...