A Unified Framework for Correlation Mining in Ultra-High Dimension-Reference-Cited by-同舟云学术

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A Unified Framework for Correlation Mining in Ultra-High Dimension

Published:2023-01 Issue:1 Volume:69 Page:334-382
ISSN:0018-9448
Container-title:IEEE Transactions on Information Theory
language:
Short-container-title:IEEE Trans. Inform. Theory

Author:

Wei Yun¹,Rajaratnam Bala²,Heroiii Alfred O.³^ORCID

Affiliation:

1. Department of Mathematics, University of Michigan, Ann Arbor, MI, USA

2. Department of Statistics, University of California at Davis, Davis, CA, USA

3. Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI, USA

Funder

U.S. Army Research Office

U.S. National Science Foundation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Library and Information Sciences,Computer Science Applications,Information Systems

Link

https://ieeexplore.ieee.org/ielam/18/9997158/9863848-aam.pdf

Reference44 articles.

1. Large Dynamic Covariance Matrices

2. The clique operator on cographs and serial graphs

3. Estimation of graphical models through structured norm minimization;tarzanagh;J Mach Learn Res,2018

4. Nonnormal Multivariate Distributions: Inference Based on Elliptically Contoured Distributions

5. An adaptable generalization of Hotelling’s $T^{2}$ test in high dimension

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