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IJCNN
2008
IEEE
16 years 1 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
16 years 1 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
IROS
2007
IEEE
157views Robotics» more  IROS 2007»
16 years 1 months ago
Autonomous blimp control using model-free reinforcement learning in a continuous state and action space
— In this paper, we present an approach that applies the reinforcement learning principle to the problem of learning height control policies for aerial blimps. In contrast to pre...
Axel Rottmann, Christian Plagemann, Peter Hilgers,...
AIED
2007
Springer
16 years 1 months ago
Learning Engagement: What Actions of Learners Could Best Predict It?
One important aspect of motivation is engagement. In order to learn, students need to be engaged in the learning activities. However, that does not always happen due to various fac...
Mihaela Cocea
AIED
2005
Springer
16 years 29 days ago
On Using Learning Curves to Evaluate ITS
Measuring the efficacy of ITS can be hard because there are many confounding factors: short, well-isolated studies suffer from insufficient interaction with the system, while longe...
Brent Martin, Kenneth R. Koedinger, Antonija Mitro...