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- Title
An accelerated distributed method with inexact model of relative smoothness and strong convexity.
- Authors
Zhang, Xuexue; Liu, Sanyang; Zhao, Nannan
- Abstract
Distributed optimisation methods are widely applied in many systems where agents cooperate with each other to minimise a sum‐type problem over a connected network. An accelerated distributed method based on the inexact model of relative smoothness and strong convexity is introduced by the authors. The authors demonstrate that the proposed method can converge to the optimal solution at the linear rate 1(1+1/(4κg))2 $\frac{1}{{(1+1/(4\sqrt{{\kappa }_{g}}))}^{2}}$ and achieve the optimal gradient computation complexity and the near optimal communication complexity, where κg denotes the global condition number. Finally, the numerical experiments are provided to validate the theoretical results and further show the efficacy of the proposed method.
- Subjects
COMPUTATIONAL complexity
- Publication
IET Signal Processing (Wiley-Blackwell), 2023, Vol 17, Issue 4, p1
- ISSN
1751-9675
- Publication type
Article
- DOI
10.1049/sil2.12199