963 search results - page 3 / 193 » Active Learning by Labeling Features |
ICDM
2010
IEEE
13 years 2 months ago
2010
IEEE
In active learning, where a learning algorithm has to purchase the labels of its training examples, it is often assumed that there is only one labeler available to label examples, ...
PR
2007
13 years 4 months ago
2007
In relevance feedback algorithms, selective sampling is often used to reduce the cost of labeling and explore the unlabeled data. In this paper, we proposed an active learning alg...
IJCAI
2003
13 years 6 months ago
2003
Multi-view learners reduce the need for labeled data by exploiting disjoint sub-sets of features (views), each of which is sufficient for learning. Such algorithms assume that eac...
SDM
2012
SIAM
11 years 7 months ago
2012
SIAM
To date, many active learning techniques have been developed for acquiring labels when training data is limited. However, an important aspect of the problem has often been neglect...
PAMI
2006
13 years 5 months ago
2006
Multiple-instance problems arise from the situations where training class labels are attached to sets of samples (named bags), instead of individual samples within each bag (called...