Convergence Analysis of Distributed Gradient Descent Algorithms With One and Two Momentum Terms

For the centralized optimization, it is well known that adding one momentum term (also called the heavy-ball method) can obtain a faster convergence rate than the gradient method. However, for the distributed counterpart, there is quite few results about the effect of added momentum terms on the con...

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Vydané v:	IEEE transactions on cybernetics Ročník 54; číslo 3; s. 1511 - 1522
Hlavní autori:	Liu, Bing, Chai, Li, Yi, Jingwen
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States IEEE 01.03.2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Algorithms Control theory Convergence Convergence rate Cost function distributed optimization Linear programming Momentum momentum term Network topology Newton method Privacy Routh criterion Signal processing algorithms
ISSN:	2168-2267, 2168-2275, 2168-2275
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