719 search results - page 1 / 144 » Discriminative learning for differing training and test dist... |
ICML
2007
IEEE
14 years 5 months ago
2007
IEEE
We address classification problems for which the training instances are governed by a distribution that is allowed to differ arbitrarily from the test distribution--problems also ...
ICML
2007
IEEE
14 years 5 months ago
2007
IEEE
In supervised learning, we commonly assume that training and test data are sampled from the same distribution. However, this assumption can be violated in practice and then standa...
PAKDD
2005
ACM
13 years 10 months ago
2005
ACM
Abstract. Discriminative and generative methods provide two distinct approaches to machine learning classification. One advantage of generative approaches is that they naturally mo...
EMNLP
2006
13 years 5 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...
ICPR
2004
IEEE
14 years 5 months ago
2004
IEEE
: Significant progress has been made by the computer vision community in recent years along two fronts: (i) developing complex spatial-temporal models for object registration and t...