A Stochastic Second-Order Proximal Method for Distributed Optimization-Reference-Cited by-同舟云学术

A Stochastic Second-Order Proximal Method for Distributed Optimization

Published:2023 Issue: Volume:7 Page:1405-1410
ISSN:2475-1456
Container-title:IEEE Control Systems Letters
language:
Short-container-title:IEEE Control Syst. Lett.

Author:

Qiu Chenyang¹^ORCID,Zhu Shanying²^ORCID,Ou Zichong¹^ORCID,Lu Jie³^ORCID

Affiliation:

1. School of Information Science and Technology, ShanghaiTech University, Shanghai, China

2. Department of Automation and the Key Laboratory of System Control and Information Processing, Shanghai Jiao Tong University, Shanghai, China

3. School of Information Science and Technology and the Shanghai Engineering Research Center of Energy Efficient and Custom AI IC, ShanghaiTech University, Shanghai, China

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Control and Optimization,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/7782633/9828546/10044149.pdf?arnumber=10044149

Reference19 articles.

1. A Second-Order Proximal Algorithm for Consensus Optimization

2. Distributed Stochastic Consensus Optimization With Momentum for Nonconvex Nonsmooth Problems

3. Accelerated gradient methods and dual decomposition in distributed model predictive control

4. Distributed optimization and statistical learning via the alternating direction method of multipliers;boyd;Foundations and Trends in Machine Learning,2011

5. A Distributed Stochastic Proximal-Gradient Algorithm for Composite Optimization

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