1455 search results - page 51 / 291 » Exploiting Myopic Learning |
ESANN
2006
15 years 1 months ago
2006
In this presentation we show the semi-supervised learning with two input sources can be transformed into a maximum margin problem to be similar to a binary SVM. Our formulation exp...
134
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CVPR
2012
IEEE
13 years 2 months ago
2012
IEEE
Active learning aims to reduce the amount of labels required for classification. The main difficulty is to find a good trade-off between exploration and exploitation of the lab...
AIMSA
2008
Springer
15 years 6 months ago
2008
Springer
Abstract. Computational Grids provide a widely distributed computing environment suitable for randomized SAT solving. This paper develops techniques for incorporating learning, kno...
102
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ICML
2001
IEEE
16 years 19 days ago
2001
IEEE
Hierarchical reinforcement learning (RL) is a general framework which studies how to exploit the structure of actions and tasks to accelerate policy learning in large domains. Pri...
ICCBR
2009
Springer
15 years 6 months ago
2009
Springer
Positive transfer learning (TL) occurs when, after gaining experience from learning how to solve a (source) task, the same learner can exploit this experience to improve performanc...