79 search results - page 5 / 16 » Active learning of label ranking functions |
NIPS
2007
15 years 10 days ago
2007
We present a general boosting method extending functional gradient boosting to optimize complex loss functions that are encountered in many machine learning problems. Our approach...
92
Voted
IJCV
2011
14 years 5 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
2008
ACM
15 years 11 months ago
2008
ACM
We consider the problem of ranking refinement, i.e., to improve the accuracy of an existing ranking function with a small set of labeled instances. We are, particularly, intereste...
126
Voted
CVPR
2009
IEEE
16 years 6 months ago
2009
IEEE
Active learning strategies can be useful when manual labeling
effort is scarce, as they select the most informative
examples to be annotated first. However, for visual category
...
ECIR
2009
Springer
15 years 8 months ago
2009
Springer
Abstract. Learning ranking functions is crucial for solving many problems, ranging from document retrieval to building recommendation systems based on an individual user’s prefer...