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AI
2002
Springer
14 years 9 months ago
Learning cost-sensitive active classifiers
Most classification algorithms are "passive", in that they assign a class label to each instance based only on the description given, even if that description is incompl...
Russell Greiner, Adam J. Grove, Dan Roth
DGO
2003
111views Education» more  DGO 2003»
14 years 11 months ago
Assessing the Usefulness and Usability of Online Learning Activities: MapStats for Kids
MapStats for Kids is concerned with the development of online learning activities based on data from the FedStats web portal. The development of these web applications requires th...
Sven Fuhrmann, John Bosley, Roger Downs, Mark Gahe...
FOIKS
2008
Springer
15 years 6 months ago
Cost-minimising strategies for data labelling : optimal stopping and active learning
Supervised learning deals with the inference of a distribution over an output or label space $\CY$ conditioned on points in an observation space $\CX$, given a training dataset $D$...
Christos Dimitrakakis, Christian Savu-Krohn
ICDM
2008
IEEE
172views Data Mining» more  ICDM 2008»
15 years 4 months ago
Active Learning of Equivalence Relations by Minimizing the Expected Loss Using Constraint Inference
Selecting promising queries is the key to effective active learning. In this paper, we investigate selection techniques for the task of learning an equivalence relation where the ...
Steffen Rendle, Lars Schmidt-Thieme
CIKM
2010
Springer
14 years 7 months ago
Combining link and content for collective active learning
In this paper, we study a novel problem Collective Active Learning, in which we aim to select a batch set of "informative" instances from a networking data set to query ...
Lixin Shi, Yuhang Zhao, Jie Tang