Learning rate of support vector machine for ranking

Heng Chen; Di Rong Chen

doi:10.1016/j.jat.2014.08.004

Learning rate of support vector machine for ranking

Heng Chen^*
, Di Rong Chen

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

6 Scopus citations

Abstract

The ranking problem has received increasing attention in both the statistical and machine learning literature. This paper considers support vector machines for ranking. Under some mild conditions, a learning rate is established.

Original language	English
Pages (from-to)	57-68
Number of pages	12
Journal	Journal of Approximation Theory
Volume	188
DOIs	https://doi.org/10.1016/j.jat.2014.08.004
State	Published - 1 Dec 2014
Externally published	Yes

Keywords

Excess risk
Ranking rule
Support vector machine
U-statistic

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10.1016/j.jat.2014.08.004

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title = "Learning rate of support vector machine for ranking",

abstract = "The ranking problem has received increasing attention in both the statistical and machine learning literature. This paper considers support vector machines for ranking. Under some mild conditions, a learning rate is established.",

keywords = "Excess risk, Ranking rule, Support vector machine, U-statistic",

author = "Heng Chen and Chen, \{Di Rong\}",

note = "Publisher Copyright: {\textcopyright} 2014 Elsevier Inc.",

year = "2014",

month = dec,

day = "1",

doi = "10.1016/j.jat.2014.08.004",

language = "英语",

volume = "188",

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journal = "Journal of Approximation Theory",

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T1 - Learning rate of support vector machine for ranking

AU - Chen, Heng

AU - Chen, Di Rong

PY - 2014/12/1

Y1 - 2014/12/1

N2 - The ranking problem has received increasing attention in both the statistical and machine learning literature. This paper considers support vector machines for ranking. Under some mild conditions, a learning rate is established.

AB - The ranking problem has received increasing attention in both the statistical and machine learning literature. This paper considers support vector machines for ranking. Under some mild conditions, a learning rate is established.

KW - Excess risk

KW - Ranking rule

KW - Support vector machine

KW - U-statistic

UR - https://www.scopus.com/pages/publications/84908089350

U2 - 10.1016/j.jat.2014.08.004

DO - 10.1016/j.jat.2014.08.004

M3 - 文章

AN - SCOPUS:84908089350

SN - 0021-9045

VL - 188

SP - 57

EP - 68

JO - Journal of Approximation Theory

JF - Journal of Approximation Theory

ER -

Learning rate of support vector machine for ranking

Abstract

Keywords

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