79 search results - page 3 / 16 » Active learning of label ranking functions |
CVPR
2007
IEEE
13 years 10 months ago
2007
IEEE
Interactively learning from a small sample of unlabeled examples is an enormously challenging task, one that often arises in vision applications. Relevance feedback and more recen...
ICML
2010
IEEE
13 years 7 months ago
2010
IEEE
This paper introduces two new methods for label ranking based on a probabilistic model of ranking data, called the Plackett-Luce model. The idea of the first method is to use the ...
NIPS
2003
13 years 7 months ago
2003
Label ranking is the task of inferring a total order over a predefined set of labels for each given instance. We present a general framework for batch learning of label ranking f...
ECML
2006
Springer
13 years 10 months ago
2006
Springer
Label ranking studies the problem of learning a mapping from instances to rankings over a predefined set of labels. We approach this setting from a case-based perspective and propo...
ICML
2009
IEEE
14 years 7 months ago
2009
IEEE
We propose an importance weighting framework for actively labeling samples. This technique yields practical yet sound active learning algorithms for general loss functions. Experi...