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CVPR
2009
IEEE
14 years 1 months ago
Imbalanced RankBoost for efficiently ranking large-scale image/video collections
Ranking large scale image and video collections usually expects higher accuracy on top ranked data, while tolerates lower accuracy on bottom ranked ones. In view of this, we propo...
Michele Merler, Rong Yan, John R. Smith
PAMI
2008
139views more  PAMI 2008»
13 years 9 months ago
A Fast Algorithm for Learning a Ranking Function from Large-Scale Data Sets
We consider the problem of learning a ranking function that maximizes a generalization of the Wilcoxon-Mann-Whitney statistic on the training data. Relying on an -accurate approxim...
Vikas C. Raykar, Ramani Duraiswami, Balaji Krishna...
CORR
2008
Springer
116views Education» more  CORR 2008»
13 years 10 months ago
Learning to rank with combinatorial Hodge theory
Abstract. We propose a number of techniques for learning a global ranking from data that may be incomplete and imbalanced -- characteristics that are almost universal to modern dat...
Xiaoye Jiang, Lek-Heng Lim, Yuan Yao, Yinyu Ye
SDM
2007
SIAM
169views Data Mining» more  SDM 2007»
13 years 11 months ago
Rank Aggregation for Similar Items
The problem of combining the ranked preferences of many experts is an old and surprisingly deep problem that has gained renewed importance in many machine learning, data mining, a...
D. Sculley
AI
2008
Springer
13 years 10 months ago
Label ranking by learning pairwise preferences
Preference learning is a challenging problem that involves the prediction of complex structures, such as weak or partial order relations, rather than single values. In the recent ...
Eyke Hüllermeier, Johannes Fürnkranz, We...