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Hong, M., Davood, H. and Zhao, M. (2017) Prox-PDA: The Proximal Primal-Dual Algorithm for Fast Distributed Nonconvex Optimization and Learning over Networks. Proceedings of the 34th International Conference on Machine Learning, Sydney, 6-11 August 2017, 2402-2433.

has been cited by the following article:

• TITLE: Distributed Alternating Direction Method of Multipliers for Multi-Objective Optimization

  AUTHORS: Hui Deng, Yangdong Xu

  KEYWORDS: Alternating Direction Method of Multipliers, Distributed Algorithm, Multi-Objective Optimization, Multi-Agent System

  JOURNAL NAME: Advances in Pure Mathematics, Vol.12 No.4, April 6, 2022

  ABSTRACT: In this paper, a distributed algorithm is proposed to solve a kind of multi-objective optimization problem based on the alternating direction method of multipliers. Compared with the centralized algorithms, this algorithm does not need a central node. Therefore, it has the characteristics of low communication burden and high privacy. In addition, numerical experiments are provided to validate the effectiveness of the proposed algorithm.