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...
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...
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...
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...
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 ...