Abstract and Applied Analysis

Regularized Ranking with Convex Losses and 1 -Penalty

Heng Chen and Jitao Wu

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In the ranking problem, one has to compare two different observations and decide the ordering between them. It has received increasing attention both in the statistical and machine learning literature. This paper considers 1 -regularized ranking rules with convex loss. Under some mild conditions, a learning rate is established.

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Abstr. Appl. Anal., Volume 2013, Special Issue (2013), Article ID 927827, 8 pages.

First available in Project Euclid: 26 February 2014

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Chen, Heng; Wu, Jitao. Regularized Ranking with Convex Losses and ${\ell }^{1}$ -Penalty. Abstr. Appl. Anal. 2013, Special Issue (2013), Article ID 927827, 8 pages. doi:10.1155/2013/927827. https://projecteuclid.org/euclid.aaa/1393450309

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