Approximation Analysis of Margin-Based Ranking Algorithm

Jin Luo

doi:10.4028/www.scientific.net/AMM.644-650.2286

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 644-650Approximation Analysis of Margin-Based Ranking...

Approximation Analysis of Margin-Based Ranking Algorithm

Abstract:

Ranking data points with respect to a given preference criterion is an example of a preference learning task. In this paper, we investigate the generalization performance of the regularized ranking algorithm associated with least square ranking loss in a reproducing kernel Hilbert space, and use the method of computing hold-out estimates for the proposed algorithm. Based on using the hold-out method, we obtain fast learning rate for this algorithm.

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Periodical:

Applied Mechanics and Materials (Volumes 644-650)

Pages:

2286-2289

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.644-650.2286

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Online since:

September 2014

Authors:

Jin Luo*

Keywords:

Manifold Learning, Ranking Algorithm

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