A projected decentralized variance-reduction algorithm for constrained optimization problems-Reference-Cited by-同舟云学术

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A projected decentralized variance-reduction algorithm for constrained optimization problems

Published:2023-10-17 Issue:2 Volume:36 Page:913-928
ISSN:0941-0643
Container-title:Neural Computing and Applications
language:en
Short-container-title:Neural Comput & Applic

Author:

Deng Shaojiang,Gao Shanfu,Lü Qingguo^ORCID,Li Yantao,Li Huaqing

Funder

Key Laboratory of Industrial Internet of Things & Networked Control, Ministry of Education

Shaanxi Province Postdoctoral Science Foundation

National Natural Science Foundation of China

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Link

https://link.springer.com/content/pdf/10.1007/s00521-023-09067-x.pdf

Reference55 articles.

1. Luan L, Qin S (2022) Neurodynamic algorithms for constrained distributed convex optimization over fixed or switching topology with time-varying communication delay. Neural Comput Appl. https://doi.org/10.1007/s00521-022-07399-8

2. Blatt D, Hero AO (2006) Energy-based sensor network source localization via projection onto convex sets. IEEE Trans Signal Process 54(9):3614–3619

3. He X, Yu J, Huang T, Li C (2019) Distributed power management for dynamic economic dispatch in the multimicrogrids environ-ment. IEEE Trans Control Syst Technol 27(4):1651–1658

4. Maros M and Jalden J (2019) ECO-PANDA: A computationally economic, geometrically converging dual optimization method on time-varying undirected graphs, Proceedings of the 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Brighton, United Kingdom , May 2019, pp. 5257-5261

5. Wen X, Wang Y, Qin S (2021) A nonautonomous-differential-inclusion neurodynamic approach for nonsmooth distributed optimization on multi-agent systems. Neural Comput Appl 33(20):13909–13920

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