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