21 search results - page 3 / 5 » Active learning for ranking through expected loss optimizati... |
142
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KDD
2009
ACM
16 years 4 months ago
2009
ACM
Labeling text data is quite time-consuming but essential for automatic text classification. Especially, manually creating multiple labels for each document may become impractical ...
135
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ICIP
2005
IEEE
16 years 6 months ago
2005
IEEE
We describe an enhanced method for the selection of optimal sensor actions in a probabilistic state estimation framework. We apply this to the selection of optimal focal lengths f...
159
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IJCV
2011
14 years 11 months ago
2011
Abstract We present an active learning framework that predicts the tradeoff between the effort and information gain associated with a candidate image annotation, thereby ranking un...
166
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WWW
2011
ACM
14 years 11 months ago
2011
ACM
Gradient Boosted Regression Trees (GBRT) are the current state-of-the-art learning paradigm for machine learned websearch ranking — a domain notorious for very large data sets. ...
147
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CIKM
2009
Springer
15 years 11 months ago
2009
Springer
Traditional boosting algorithms for the ranking problems usually employ the pairwise approach and convert the document rating preference into a binary-value label, like RankBoost....