313 search results - page 24 / 63 » Hierarchical sampling for active learning |
ICML
2010
IEEE
13 years 12 months ago
2010
IEEE
We consider the problem of multi-task reinforcement learning where the learner is provided with a set of tasks, for which only a small number of samples can be generated for any g...
CEAS
2007
Springer
14 years 2 months ago
2007
Springer
Active learning methods seek to reduce the number of labeled examples needed to train an effective classifier, and have natural appeal in spam filtering applications where trustwo...
ICDM
2010
IEEE
13 years 8 months ago
2010
IEEE
Active learning has been proven a reliable strategy to reduce manual efforts in training data labeling. Such strategies incorporate the user as oracle: the classifier selects the m...
PAMI
2006
13 years 10 months ago
2006
In this paper we present a variational Bayes (VB) framework for learning continuous hidden Markov models (CHMMs), and we examine the VB framework within active learning. Unlike a ...
IIR
2010
14 years 8 days ago
2010
Given a classifier trained on relatively few training examples, active learning (AL) consists in ranking a set of unlabeled examples in terms of how informative they would be, if ...