79 search results - page 3 / 16 » Active learning of label ranking functions |
122
Voted
CVPR
2007
IEEE
15 years 2 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...
94
Voted
ICML
2010
IEEE
14 years 12 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
15 years 8 days 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
15 years 2 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...
80
Voted
ICML
2009
IEEE
15 years 11 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...