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Abstract: We propose efficient algorithms for learning ranking functions from order constraints between sets---i.e. classes---of training samples. Our algorithms may be used for maximizing the generalized Wilcoxon Mann Whitney statistic that accounts for the partial ordering of the classes: special cases include maximizing the area under the ROC curve for binary classification and its generalization for ordinal regression. Experiments on public benchmarks indicate that: (a) the proposed algorithm... (Update)
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BibTeX entry: (Update)
G. Fung, R. Rosales, and B. Krishnapuram. Learning rankings via convex hull separation. In Advances in Neural Information Processing Systems 18, 2006. http://citeseer.ist.psu.edu/fung06learning.html More
@misc{ fung06learning,
author = "G. Fung and R. Rosales and B. Krishnapuram",
title = "Learning rankings via convex hull separation",
text = "G. Fung, R. Rosales, and B. Krishnapuram. Learning rankings via convex
hull separation. In Advances in Neural Information Processing Systems 18,
2006.",
year = "2006",
url = "citeseer.ist.psu.edu/fung06learning.html" }
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