Loopless Variance Reduced Stochastic ADMM for Equality Constrained Problems in IoT Applications

The alternating direction method of multipliers (ADMMs) is an efficient optimization method for solving equality constrained problems in Internet of Things (IoT) applications. Recently, several stochastic variance reduced ADMM algorithms (e.g., SVRG-ADMM) have made exciting progress, such as linear...

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Vydané v:	IEEE internet of things journal Ročník 9; číslo 3; s. 2293 - 2303
Hlavní autori:	Liu, Yuanyuan, Geng, Jiacheng, Shang, Fanhua, An, Weixin, Liu, Hongying, Zhu, Qi
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Piscataway IEEE 01.02.2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Algorithms Alternating direction method of multipliers (ADMMs) Convergence Convex functions Internet of Things loopless algorithm Minimization momentum acceleration Optimization Optimization methods stochastic variance reduced gradient (SVRG) Training Upper bound Variance
ISSN:	2327-4662, 2327-4662
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