Ranking

Description

Ranking is a general problem in machine learning. A commonly used measure of the ranking quality of an algorithm is the Area Under the ROC Curve (AUC).

Related Publications

Stephen Boyd, Corinna Cortes, Mehryar Mohri, and Ana Radovanovic.
Accuracy at the top.
In Advances in Neural Information Processing Systems (NIPS 2012). Lake Tahoe, Nevada, 2012. MIT Press.

Nir Ailon and Mehryar Mohri.
Preference-based learning to rank.
Machine Learning Journal, to appear, 2010.

Nir Ailon and Mehryar Mohri.
An efficient reduction of ranking to classification.
In Proceedings of The 21st Annual Conference on Learning Theory (COLT 2008). Helsinki, Finland, July 2008. Omnipress.

Corinna Cortes, Mehryar Mohri, and Ashish Rastogi.
Magnitude-preserving ranking algorithms.
In Proceedings of the Twenty-fourth International Conference on Machine Learning (ICML 2007). Oregon State University, Corvallis, OR, June 2007.

Corinna Cortes, Mehryar Mohri, and Ashish Rastogi.
An Alternative Ranking Problem for Search Engines.
In Proceedings of the 6th Workshop on Experimental Algorithms (WEA 2007). volume 4525 of Lecture Notes in Computer Science, pages 1-21, Rome, Italy, June 2007. Springer-Verlag, Heidelberg, Germany.

Cynthia Rudin, Corinna Cortes, Mehryar Mohri, and Robert E. Schapire.
Margin-Based Ranking Meets Boosting in the Middle.
In Proceedings of The 18th Annual Conference on Computational Learning Theory (COLT 2005). volume 3359 of Lecture Notes in Computer Science, pages 63-78, Bertinoro, Italy, June 2005. Springer, Heidelberg, Germany.

Corinna Cortes and Mehryar Mohri.
Confidence Intervals for the Area under the ROC Curve.
In Advances in Neural Information Processing Systems (NIPS 2004). volume to appear, Vancouver, Canada, 2005. MIT Press.

Corinna Cortes and Mehryar Mohri.
AUC Optimization vs. Error Rate Minimization.
In Advances in Neural Information Processing Systems (NIPS 2003). volume 16, Vancouver, Canada, 2004. MIT Press.

	Stephen Boyd, Corinna Cortes, Mehryar Mohri, and Ana Radovanovic. Accuracy at the top. In Advances in Neural Information Processing Systems (NIPS 2012). Lake Tahoe, Nevada, 2012. MIT Press.
	Nir Ailon and Mehryar Mohri. Preference-based learning to rank. Machine Learning Journal, to appear, 2010.
	Nir Ailon and Mehryar Mohri. An efficient reduction of ranking to classification. In Proceedings of The 21st Annual Conference on Learning Theory (COLT 2008). Helsinki, Finland, July 2008. Omnipress.
	Corinna Cortes, Mehryar Mohri, and Ashish Rastogi. Magnitude-preserving ranking algorithms. In Proceedings of the Twenty-fourth International Conference on Machine Learning (ICML 2007). Oregon State University, Corvallis, OR, June 2007.
	Corinna Cortes, Mehryar Mohri, and Ashish Rastogi. An Alternative Ranking Problem for Search Engines. In Proceedings of the 6th Workshop on Experimental Algorithms (WEA 2007). volume 4525 of Lecture Notes in Computer Science, pages 1-21, Rome, Italy, June 2007. Springer-Verlag, Heidelberg, Germany.
	Cynthia Rudin, Corinna Cortes, Mehryar Mohri, and Robert E. Schapire. Margin-Based Ranking Meets Boosting in the Middle. In Proceedings of The 18th Annual Conference on Computational Learning Theory (COLT 2005). volume 3359 of Lecture Notes in Computer Science, pages 63-78, Bertinoro, Italy, June 2005. Springer, Heidelberg, Germany.
	Corinna Cortes and Mehryar Mohri. Confidence Intervals for the Area under the ROC Curve. In Advances in Neural Information Processing Systems (NIPS 2004). volume to appear, Vancouver, Canada, 2005. MIT Press.
	Corinna Cortes and Mehryar Mohri. AUC Optimization vs. Error Rate Minimization. In Advances in Neural Information Processing Systems (NIPS 2003). volume 16, Vancouver, Canada, 2004. MIT Press.