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Auto-weighted 2-dimensional maximum margin criterion
Zhang, Han1; Nie, Feiping1; Zhang, Rui1; Li, Xuelong2; Nie, Feiping (feipingnie@gmail.com)
Source PublicationPattern Recognition
Contribution Rank2

As a hot topic in machine learning, supervised learning is applied to both classification and recognition frequently. However, parameter-tuning in most supervised methods is a laborious work due to its complexity and unpredictability. In this paper, we propose an auto-weighted approach, termed as auto-weighted 2-dimensional maximum margin criterion, which updates the introduced weight in each iteration automatically to leverage the associated terms, so that the weight becomes insensitive to initialization. In addition, the proposed method extracts features from 2-order data directly, i.e., image data. Moreover, we have an observation that the objective value in the proposed method could directly reflect the performance in classification task under the varying dimensionality, which is much beneficial to selection of the optimal dimensionality. Extensive experiments on several datasets are conducted to validate that our method is of great superiority compared to other approaches. © 2018 Elsevier Ltd

Indexed BySCI ; EI
WOS IDWOS:000442172200017
EI Accession Number20182405301511
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Document Type期刊论文
Corresponding AuthorNie, Feiping (feipingnie@gmail.com)
Affiliation1.School of Computer Science and Center for OPTical IMagery Analysis and Learning (OPTIMAL), Northwestern Polytechnical University, Xi'an; Shaanxi; 710072, China
2.Center for OPTical IMagery Analysis and Learning (OPTIMAL), State Key Laboratory of Transient Optics and Photonics, Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an; Shaanxi; 710119, China
Recommended Citation
GB/T 7714
Zhang, Han,Nie, Feiping,Zhang, Rui,et al. Auto-weighted 2-dimensional maximum margin criterion[J]. Pattern Recognition,2018,83:220-229.
APA Zhang, Han,Nie, Feiping,Zhang, Rui,Li, Xuelong,&Nie, Feiping .(2018).Auto-weighted 2-dimensional maximum margin criterion.Pattern Recognition,83,220-229.
MLA Zhang, Han,et al."Auto-weighted 2-dimensional maximum margin criterion".Pattern Recognition 83(2018):220-229.
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