5302 search results - page 211 / 1061 » Learning How to Separate |
123
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ICML
2008
IEEE
16 years 5 months ago
2008
IEEE
Sampling is a popular way of scaling up machine learning algorithms to large datasets. The question often is how many samples are needed. Adaptive stopping algorithms monitor the ...
102
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UM
2007
Springer
15 years 10 months ago
2007
Springer
There has been increasing interest in using games for education, but little investigation of how to model student learning within games [cf. 6]. We investigate how existing techniq...
110
Voted
HAIS
2009
Springer
15 years 8 months ago
2009
Springer
One of the most important challenges in supervised learning is how to evaluate the quality of the models evolved by different machine learning techniques. Up to now, we have relied...
130
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ECIR
2010
Springer
15 years 5 months ago
2010
Springer
Abstract. This paper explores how to predict query difficulty for contextual image retrieval. We reformulate the problem as the task of predicting how difficult to represent a quer...
153
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MCS
2005
Springer
15 years 9 months ago
2005
Springer
We study how the error of an ensemble regression estimator can be decomposed into two components: one accounting for the individual errors and the other accounting for the correlat...