2884 search results - page 188 / 577 » Evaluating learning algorithms and classifiers |
144
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ROBOCUP
2007
Springer
15 years 10 months ago
2007
Springer
Reinforcement learning is a paradigm under which an agent seeks to improve its policy by making learning updates based on the experiences it gathers through interaction with the en...
134
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CIKM
2006
Springer
15 years 8 months ago
2006
Springer
In practical classification, there is often a mix of learnable and unlearnable classes and only a classifier above a minimum performance threshold can be deployed. This problem is...
155
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ESANN
2006
15 years 5 months ago
2006
In this article, we extend a local prototype-based learning model by active learning, which gives the learner the capability to select training samples during the model adaptation...
117
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ICML
2006
IEEE
16 years 5 months ago
2006
IEEE
The general approach for automatically driving data collection using information from previously acquired data is called active learning. Traditional active learning addresses the...
155
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CVPR
2007
IEEE
16 years 6 months ago
2007
IEEE
We propose a method for learning using a set of feature representations which retrieve different amounts of information at different costs. The goal is to create a more efficient ...