Regret analysis of an online majorized semi-proximal ADMM for online composite optimization
Author:
Funder
National Key R &D Program of China
Natural Science Foundation of China
Dalian High-Level Talent Innovation Project
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s10898-024-01365-5.pdf
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4. Chen, L., Defeng, S., Kim-Chuan, T.: An efficient inexact symmetric GaussCSeidel based majorized ADMM for high-dimensional convex composite conic programming. Math. Program. 161, 237–270 (2017)
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1. Online composite optimization with time-varying regularizers;Journal of the Franklin Institute;2024-07
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