683 search results - page 2 / 137 » Active Sampling for Feature Selection |
KI
2007
Springer
13 years 5 months ago
2007
Springer
Detecting unknown worms is a challenging task. Extant solutions, such as anti-virus tools, rely mainly on prior explicit knowledge of specific worm signatures. As a result, after t...
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...
ECML
2006
Springer
13 years 9 months ago
2006
Springer
Abstract. We propose a novel active learning strategy based on the compression framework of [9] for label ranking functions which, given an input instance, predict a total order ov...
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...
GECCO
2008
Springer
13 years 6 months ago
2008
Springer
Selective sampling is a form of active learning which can reduce the cost of training by only drawing informative data points into the training set. This selected training set is ...