L1-norm-based maximum margin criterion

被引：0

作者：

Chen S.-B. ^{[1
,2
]}

Chen D.-R. ^{[1
,2
]}

Luo B. ^{[1
,2
]}

机构：

[1] School of Computer Science and Technology, Anhui University, Hefei, 230601, Anhui

[2] Key Laboratory for Industrial Image Processing and Analysis of Anhui Province, Hefei, 230039, Anhui

来源：

Tien Tzu Hsueh Pao/Acta Electronica Sinica | 2016年 / 44卷 / 06期

关键词：

Dimensionality reduction; L1-norm; Linear projection; Maximum margin criterion (MMC);

D O I：

10.3969/j.issn.0372-2112.2016.06.018

中图分类号：

学科分类号：

摘要：

When performing dimensionality reduction with linear projections,maximum margin criterion (MMC) is often affected by outliers and noises due to L2-norm.In this paper,L1-norm-based maximum margin criterion (MMC-L1) is proposed for dimensionality reduction.It makes full use of Maximum Margin Criterion and strong robustness of L1-norm to outliers and noises.A rapid iterative optimization algorithm,with its proof of monotonic convergence to local optimum,is given.Experiments on several public image databases verify the robustness and efficiency of the proposed method. © 2016, Chinese Institute of Electronics. All right reserved.

引用

页码：1383 / 1388

页数：5

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