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3. Burges, C.J., Shaked, T., Renshaw, E., Lazier, A., Deeds, M., Hamilton, N., Hullender, G.:
Learning to rank using gradient descent. In: Proceedings of the 22nd International Conference
on Machine Learning (ICML 2005), pp. 89-96 (2005)
4. Cao, Z., Qin, T., Liu, T.Y., Tsai, M.F., Li, H.: Learning to rank: from pairwise approach to
listwise approach. In: Proceedings of the 24th International Conference on Machine Learning
(ICML 2007), pp. 129-136 (2007)
5. Clemencon, S., Lugosi, G., Vayatis, N.: Ranking and empirical minimization of u-statistics.
The Annals of Statistics 36 (2), 844-874 (2008)
6. Cossock, D., Zhang, T.: Subset ranking using regression. In: Proceedings of the 19th Annual
Conference on Learning Theory (COLT 2006), pp. 605-619 (2006)
7. Freund, Y., Iyer, R., Schapire, R., Singer, Y.: An efficient boosting algorithm for combining
preferences. Journal of Machine Learning Research 4 , 933-969 (2003)
8. Herbrich, R., Obermayer, K., Graepel, T.: Large margin rank boundaries for ordinal regres-
sion. In: Advances in Large Margin Classifiers, pp. 115-132 (2000)
9. Joachims, T.: Optimizing search engines using clickthrough data. In: Proceedings of the 8th
ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD
2002), pp. 133-142 (2002)
10. Lan, Y., Liu, T.Y., Ma, Z.M., Li, H.: Statistical consistency of ranking methods. Tech. rep.,
Microsoft Research (2010)
11. Sun, Z., Qin, T., Tao, Q., Wang, J.: Robust sparse rank learning for non-smooth ranking mea-
sures. In: Proceedings of the 32nd Annual International ACM SIGIR Conference on Research
and Development in Information Retrieval (SIGIR 2009), pp. 259-266 (2009)
12. Xia, F., Liu, T.Y., Li, H.: Statistical consistency of top-k ranking. In: Advances in Neural
Information Processing Systems 22 (NIPS 2009), pp. 2098-2106 (2010)
13. Xia, F., Liu, T.Y., Wang, J., Zhang, W., Li, H.: Listwise approach to learning to rank—theorem
and algorithm. In: Proceedings of the 25th International Conference on Machine Learning
(ICML 2008), pp. 1192-1199 (2008)
14. Zhang, T.: Statistical behavior and consistency of classification methods based on convex risk
minimization. Annual Statistics 32 (1), 56-85 (2004)
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