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2012 Approximation Analysis of Gradient Descent Algorithm for Bipartite Ranking
Hong Chen, Fangchao He, Zhibin Pan
J. Appl. Math. 2012: 1-13 (2012). DOI: 10.1155/2012/189753

Abstract

We introduce a gradient descent algorithm for bipartite ranking with general convex losses. The implementation of this algorithm is simple, and its generalization performance is investigated. Explicit learning rates are presented in terms of the suitable choices of the regularization parameter and the step size. The result fills the theoretical gap in learning rates for ranking problem with general convex losses.

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Hong Chen. Fangchao He. Zhibin Pan. "Approximation Analysis of Gradient Descent Algorithm for Bipartite Ranking." J. Appl. Math. 2012 1 - 13, 2012. https://doi.org/10.1155/2012/189753

Information

Published: 2012
First available in Project Euclid: 14 December 2012

zbMATH: 1251.90314
MathSciNet: MR2948147
Digital Object Identifier: 10.1155/2012/189753

Rights: Copyright © 2012 Hindawi

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