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» Active Learning with Irrelevant Examples
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ML
2008
ACM
134views Machine Learning» more  ML 2008»
14 years 11 months ago
Multilabel classification via calibrated label ranking
Label ranking studies the problem of learning a mapping from instances to rankings over a predefined set of labels. Hitherto existing approaches to label ranking implicitly operat...
Johannes Fürnkranz, Eyke Hüllermeier, En...
PKDD
2009
Springer
184views Data Mining» more  PKDD 2009»
15 years 4 months ago
Boosting Active Learning to Optimality: A Tractable Monte-Carlo, Billiard-Based Algorithm
Abstract. This paper focuses on Active Learning with a limited number of queries; in application domains such as Numerical Engineering, the size of the training set might be limite...
Philippe Rolet, Michèle Sebag, Olivier Teyt...
HICSS
2008
IEEE
132views Biometrics» more  HICSS 2008»
15 years 6 months ago
Support of Case-Based Authentic Learning Activities: A Collaborative Case Commenting Tool and a Collaborative Case Builder
Cases are widely used in professional education to engage learners with examples of real world practices. Collaboration in casebased learning can add to the authenticity of the ex...
Lu Xiao, John M. Carroll, Pat Clemson, Mary Beth R...
JAIR
2006
105views more  JAIR 2006»
14 years 11 months ago
Active Learning with Multiple Views
Active learners alleviate the burden of labeling large amounts of data by detecting and asking the user to label only the most informative examples in the domain. We focus here on...
Ion Muslea, Steven Minton, Craig A. Knoblock
COLT
2006
Springer
15 years 3 months ago
Active Sampling for Multiple Output Identification
We study functions with multiple output values, and use active sampling to identify an example for each of the possible output values. Our results for this setting include: (1) Eff...
Shai Fine, Yishay Mansour