A selective review on statistical methods for massive data computation: distributed computing, subsampling, and minibatch techniques-Reference-Cited by-同舟云学术

A selective review on statistical methods for massive data computation: distributed computing, subsampling, and minibatch techniques

Published:2024-04-23 Issue:3 Volume:8 Page:163-185
ISSN:2475-4269
Container-title:Statistical Theory and Related Fields
language:en
Short-container-title:Statistical Theory and Related Fields

Author:

Li Xuetong¹,Gao Yuan¹^ORCID,Chang Hong¹,Huang Danyang²,Ma Yingying³,Pan Rui⁴,Qi Haobo⁵,Wang Feifei²,Wu Shuyuan⁶,Xu Ke⁷,Zhou Jing²,Zhu Xuening⁸,Zhu Yingqiu⁷,Wang Hansheng¹

Affiliation:

1. Guanghua School of Management, Peking University, Beijing, People's Republic of China

2. Center for Applied Statistics and School of Statistics, Renmin University of China, Beijing, People's Republic of China

3. School of Economics and Management, Beihang University, Beijing, People's Republic of China

4. School of Statistics and Mathematics, Central University of Finance and Economics, Beijing, People's Republic of China

5. School of Statistics, Beijing Normal University, Beijing, People's Republic of China

6. School of Statistics and Management, Shanghai University of Finance and Economics, Shanghai, People's Republic of China

7. School of Statistics, University of International Business and Economics, Beijing, People's Republic of China

8. School of Data Science and MOE Laboratory for National Development and Intelligent Governance, Fudan University, Shanghai, People's Republic of China

Funder

National Natural Science Foundation of China

National Statistical Science Research Project

Fundamental Research Funds for the Central Universities in UIBE

Program for Innovation Research, the disciplinary funding and the Emerging Interdisciplinary Project of Central University of Finance and Economics; and the Postdoctoral Fellowship Program of CPSF

MOE Project of Key Research Institute of Humanities and Social Sciences

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/24754269.2024.2343151

Reference193 articles.

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