Projected subgradient based distributed convex optimization with transmission noises

作者：

Highlights：

• We consider the constrained stochastic convex optimization by projected subgradient algorithm.

• A new convergence analysis approach is developed to prove the validity of the proposed algorithm.

• Convergence rate is given without specifying the gains.

摘要

•We consider the constrained stochastic convex optimization by projected subgradient algorithm.•A new convergence analysis approach is developed to prove the validity of the proposed algorithm.•Convergence rate is given without specifying the gains.

论文关键词：Distributed convex optimization,Projected subgradient algorithm,Additive noise,Polyhedric set constraint,Random inner space

论文评审过程：Received 26 January 2021, Revised 30 August 2021, Accepted 8 November 2021, Available online 29 November 2021, Version of Record 29 November 2021.

论文官网地址：https://doi.org/10.1016/j.amc.2021.126794