Dpca: Dimensionality Reduction for Discriminative Analytics of Multiple Large-Scale Datasets

Gang Wang, Jia Chen, Georgios B. Giannakis

科研成果: 书/报告/会议事项章节会议稿件同行评审

6 引用 (Scopus)

摘要

Principal component analysis (PCA) has well-documented merits for data extraction and dimensionality reduction. PCA deals with a single dataset at a time, and it is challenged when it comes to analyzing multiple datasets. Yet in certain setups, one wishes to extract the most significant information of one dataset relative to other datasets. Specifically, the interest may be on identifying or extracting features that are specific to a single target dataset but not the others. This paper presents a novel approach for such so-termed discriminative data analysis, and establishes its optimality in the least-squares sense under suitable assumptions. The criterion reveals linear combinations of variables by maximizing the ratio of the variance of the target data to that of the remainders. The novel approach solves a generalized eigenvalue problem by performing SVD just once. Numerical tests using synthetic and real datasets showcase the merits of the proposed approach relative to its competing alternatives.

源语言英语
主期刊名2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Proceedings
出版商Institute of Electrical and Electronics Engineers Inc.
2211-2215
页数5
ISBN(印刷版)9781538646588
DOI
出版状态已出版 - 10 9月 2018
已对外发布
活动2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Calgary, 加拿大
期限: 15 4月 201820 4月 2018

出版系列

姓名ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
2018-April
ISSN(印刷版)1520-6149

会议

会议2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018
国家/地区加拿大
Calgary
时期15/04/1820/04/18

引用此

Wang, G., Chen, J., & Giannakis, G. B. (2018). Dpca: Dimensionality Reduction for Discriminative Analytics of Multiple Large-Scale Datasets. 在 2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Proceedings (页码 2211-2215). 文章 8461744 (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings; 卷 2018-April). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICASSP.2018.8461744