Approximation to Stochastic Variance Reduced Gradient Langevin Dynamics by Stochastic Delay Differential Equations

doi:10.1007/s00245-022-09854-3

UM > Faculty of Science and Technology > DEPARTMENT OF MATHEMATICS

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	Approximation to Stochastic Variance Reduced Gradient Langevin Dynamics by Stochastic Delay Differential Equations
	Chen, Peng 1,2,3; Lu, Jianya 2,3; Xu, Lihu2,3
	2022-04-13
Source Publication	Applied Mathematics and Optimization
ISSN	0095-4616
Volume	85 Issue:2 Pages:15
Abstract	We study in this paper weak approximations in Wasserstein-1 distance to stochastic variance reduced gradient Langevin dynamics by stochastic delay differential equations, and obtain uniform error bounds. Our approach is via Malliavin calculus and a refined Lindeberg principle.
Keyword	Malliavin Calculus Refined Lindeberg Principle Stochastic Delay Differential Equations (Sddes) Stochastic Variance Reduced Gradient Langevin Dynamics (Svrg-ld) Wasserstein-1 Distance
DOI	10.1007/s00245-022-09854-3
URL	View the original
Indexed By	SCIE
Language	英語English
WOS Research Area	Mathematics
WOS Subject	Mathematics, Applied
WOS ID	WOS:000782327200013
Publisher	SPRINGERONE NEW YORK PLAZA, SUITE 4600 , NEW YORK, NY 10004, UNITED STATES
Scopus ID	2-s2.0-85128214959
Fulltext Access	View Full-Text via DOI View Full-Text via Web of Science View Full-Text via Scopus
Citation statistics
Document Type	Journal article
Collection	DEPARTMENT OF MATHEMATICS
Corresponding Author	Xu, Lihu
Affiliation	1.Department of Mathematics, College of Science, Nanjing University of Aeronautics and Astronautics, Nanjing, Jiangsu, China 2.Department of Mathematics, Faculty of Science and Technology, University of Macau Av. Padre Tomás Pereira, Taipa, Macao 3.UMacau Zhuhai Research Institute, Zhuhai, China
First Author Affilication	Faculty of Science and Technology; University of Macau
Corresponding Author Affilication	Faculty of Science and Technology; University of Macau
Recommended Citation GB/T 7714	Chen, Peng,Lu, Jianya,Xu, Lihu. Approximation to Stochastic Variance Reduced Gradient Langevin Dynamics by Stochastic Delay Differential Equations[J]. Applied Mathematics and Optimization, 2022, 85(2), 15.
APA	Chen, Peng., Lu, Jianya., & Xu, Lihu (2022). Approximation to Stochastic Variance Reduced Gradient Langevin Dynamics by Stochastic Delay Differential Equations. Applied Mathematics and Optimization, 85(2), 15.
MLA	Chen, Peng,et al."Approximation to Stochastic Variance Reduced Gradient Langevin Dynamics by Stochastic Delay Differential Equations".Applied Mathematics and Optimization 85.2(2022):15.

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