112 search results - page 4 / 23 » Selective generation of training examples in active meta-lea... |
HIS
2008
13 years 8 months ago
2008
Classification in imbalanced domains is a recent challenge in machine learning. We refer to imbalanced classification when data presents many examples from one class and few from ...
IJCAI
2007
13 years 8 months ago
2007
Given sensors to detect object use, commonsense priors of object usage in activities can reduce the need for labeled data in learning activity models. It is often useful, however,...
ECIR
2007
Springer
13 years 8 months ago
2007
Springer
Automated text categorisation systems learn a generalised hypothesis from large numbers of labelled examples. However, in many domains labelled data is scarce and expensive to obta...
CORR
2011
Springer
12 years 11 months ago
2011
Springer
For large, real-world inductive learning problems, the number of training examples often must be limited due to the costs associated with procuring, preparing, and storing the tra...
Publication
One of the principal bottlenecks in applying learning techniques to classification problems is the large amount of labeled training data required. Especially for images and video, ...