中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Multiview dimension reduction via Hessian multiset canonical correlations.

文献类型:期刊论文

作者Liu, Weifeng; Yang, Xinghao; Tao, Dapeng; Cheng, Jun; Tang, Yuanyan
刊名Information Fusion
出版日期2018
文献子类期刊论文
英文摘要Canonical correlation analysis (CCA) is a main technique of linear subspace approach for two-view dimension reduction by finding basis vectors with maximum correlation between the pair of variables. The shortcoming of the traditional CCA lies that it only handles data represented by two-view features and cannot reveal the nonlinear correlation relationship. In recent years, many variant algorithms have been developed to extend the capability of CCA such as discriminative CCA, sparse CCA, kernel CCA, locality preserving CCA and multiset canonical correlation analysis (MCCA). One representative work is Laplacian multiset canonical correlations (LapMCC) that employs graph Laplacian to exploit the nonlinear correlation information for multiview high-dimensional data. However, it possibly leads to poor extrapolating power because Laplacian regularization biases the solution towards a constant function. In this paper, we present Hessian multiset canonical correlations (HesMCC) for multiview dimension reduction. Hessian can properly exploit the intrinsic local geometry of the data manifold in contrast to Laplacian. HesMCC takes the advantage of Hessian and provides superior extrapolating capability and finally leverage the performance. Extensive experiments on several popular datasets for handwritten digits classification, face classification and object classification validate the effectiveness of the proposed HesMCC algorithm by comparing it with baseline algorithms including TCCA, KMUDA, MCCA and LapMCC
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语种英语
源URL[http://ir.siat.ac.cn:8080/handle/172644/13566]  
专题深圳先进技术研究院_集成所
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GB/T 7714
Liu, Weifeng,Yang, Xinghao,Tao, Dapeng,et al. Multiview dimension reduction via Hessian multiset canonical correlations.[J]. Information Fusion,2018.
APA Liu, Weifeng,Yang, Xinghao,Tao, Dapeng,Cheng, Jun,&Tang, Yuanyan.(2018).Multiview dimension reduction via Hessian multiset canonical correlations..Information Fusion.
MLA Liu, Weifeng,et al."Multiview dimension reduction via Hessian multiset canonical correlations.".Information Fusion (2018).

入库方式: OAI收割

来源:深圳先进技术研究院

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