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NIPS
2007
15 years 8 months ago
Discriminative Batch Mode Active Learning
Active learning sequentially selects unlabeled instances to label with the goal of reducing the effort needed to learn a good classifier. Most previous studies in active learning...
Yuhong Guo, Dale Schuurmans
IADIS
2004
15 years 8 months ago
Electronic case studies: a problem-based learning approach
E-Cases is an innovative approach to management development. Traditional case studies typically describe a decision or a problem in a real-life setting. E-Cases encourage students...
Philip M. Drinkwater, Christopher P. Holland, K. N...
ICMLA
2003
15 years 8 months ago
Reinforcement Learning Task Clustering
This work represents the first step towards a task library system in the reinforcement learning domain. Task libraries could be useful in speeding up the learning of new tasks th...
James L. Carroll, Todd S. Peterson, Kevin D. Seppi
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NIPS
1992
15 years 8 months ago
Explanation-Based Neural Network Learning for Robot Control
How can artificial neural nets generalize better from fewer examples? In order to generalize successfully, neural network learning methods typically require large training data se...
Tom M. Mitchell, Sebastian Thrun
AI
2007
Springer
15 years 7 months ago
Argument based machine learning
We present a novel approach to machine learning, called ABML (argumentation based ML). This approach combines machine learning from examples with concepts from the field of argum...
Martin Mozina, Jure Zabkar, Ivan Bratko