55 search results - page 6 / 11 » Assessing the Costs of Sampling Methods in Active Learning f... |
AAAI
2008
13 years 11 months ago
2008
For many machine learning solutions to complex applications, there are significant performance advantages to decomposing the overall task into several simpler sequential stages, c...
ECML
2005
Springer
14 years 2 months ago
2005
Springer
Active selection of good training examples is an important approach to reducing data-collection costs in machine learning; however, most existing methods focus on maximizing classi...
IJCAI
2001
13 years 10 months ago
2001
For many supervised learning tasks it is very costly to produce training data with class labels. Active learning acquires data incrementally, at each stage using the model learned...
PRIB
2010
Springer
13 years 7 months ago
2010
Springer
Abstract. Supervised classifiers require manually labeled training samples to classify unlabeled objects. Active Learning (AL) can be used to selectively label only “ambiguous...
ML
2007
ACM
13 years 8 months ago
2007
ACM
Which active learning methods can we expect to yield good performance in learning binary and multi-category logistic regression classifiers? Addressing this question is a natural ...