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ICML
2006
IEEE
14 years 11 months ago
Active learning via transductive experimental design
This paper considers the problem of selecting the most informative experiments x to get measurements y for learning a regression model y = f(x). We propose a novel and simple conc...
Kai Yu, Jinbo Bi, Volker Tresp
IJCNN
2008
IEEE
14 years 4 months ago
Active Meta-Learning with Uncertainty Sampling and Outlier Detection
Abstract— Meta-Learning has been used to predict the performance of learning algorithms based on descriptive features of the learning problems. Each training example in this cont...
Ricardo Bastos Cavalcante Prudêncio, Teresa ...
AIRS
2008
Springer
14 years 4 months ago
Active Learning for Online Spam Filtering
Spam filtering is defined as a task trying to label emails with spam or ham in an online situation. The online feature requires the spam filter has a strong timely generalization a...
Wuying Liu, Ting Wang
ECML
2006
Springer
14 years 1 months ago
Margin-Based Active Learning for Structured Output Spaces
In many complex machine learning applications there is a need to learn multiple interdependent output variables, where knowledge of these interdependencies can be exploited to impr...
Dan Roth, Kevin Small
IROS
2009
IEEE
155views Robotics» more  IROS 2009»
14 years 4 months ago
Active learning using mean shift optimization for robot grasping
— When children learn to grasp a new object, they often know several possible grasping points from observing a parent’s demonstration and subsequently learn better grasps by tr...
Oliver Kroemer, Renaud Detry, Justus H. Piater, Ja...