21 search results - page 3 / 5 » Active learning for ranking through expected loss optimizati... |
KDD
2009
ACM
14 years 6 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 ...
ICIP
2005
IEEE
14 years 8 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...
IJCV
2011
13 years 1 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...
WWW
2011
ACM
13 years 1 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. ...
CIKM
2009
Springer
14 years 25 days 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....