Randomized gradient-free distributed online optimization via a dynamic regret analysis

This work considers an online distributed optimization problem, with a group of agents whose local objective functions vary with time. Moreover, the value of the objective function is revealed to the corresponding agent after the decision is executed per time-step. Thus, each agent can only update t...

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Bibliographic Details
Main Authors: Pang, Yipeng, Hu, Guoqiang
Other Authors: School of Electrical and Electronic Engineering
Format: Article
Language:English
Published: 2023
Subjects:
Online Access:https://hdl.handle.net/10356/170697
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Institution: Nanyang Technological University
Language: English
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