Alternating DCA for reduced-rank multitask linear regression with covariance matrix estimation

We study a challenging problem in machine learning that is the reduced-rank multitask linear regression with covariance matrix estimation. The objective is to build a linear relationship between multiple output variables and input variables of a multitask learning process, taking into account the ge...

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Bibliographic Details
Published in:	Annals of mathematics and artificial intelligence Vol. 90; no. 7-9; pp. 809 - 829
Main Authors:	Le Thi, Hoai An, Ho, Vinh Thanh
Format:	Journal Article
Language:	English
Published:	Cham Springer International Publishing 01.09.2022 Springer Springer Nature B.V Springer Verlag
Subjects:	Algorithms Artificial Intelligence Complex Systems Computer Science Convexity Covariance matrix Critical point Machine learning Mathematics Regression analysis Regression models DCA 62J05 Reduced-rank multitask linear regression DC programming 90C90 90C26 Partial DC program Covariance matrix estimation Alternating DCA Partial DC programming
ISSN:	1012-2443, 1573-7470
Online Access:	Get full text
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