Distributed constrained optimization over unbalanced graphs and delayed gradient
In this paper, we investigate a distributed constrained optimization problem subject to convex, closed, and nonidentical set constraints over unbalanced graphs, where each agent has local access to its strongly convex objective function and collaborates, minimizing the sum of these functions. To add...
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| Vydáno v: | Journal of the Franklin Institute Ročník 362; číslo 2; s. 107466 |
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| Jazyk: | angličtina |
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01.01.2025
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| ISSN: | 0016-0032 |
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| Abstract | In this paper, we investigate a distributed constrained optimization problem subject to convex, closed, and nonidentical set constraints over unbalanced graphs, where each agent has local access to its strongly convex objective function and collaborates, minimizing the sum of these functions. To address this problem, we design a distributed projected delayed gradient algorithm by using the available delayed gradient information, which removes dependence on the current gradient information and increases iteration efficiency. Moreover, to improve communication robustness, the algorithm is only based on a row stochastic weight matrix and achieves an O(1/T) convergence rate for a non-negative and diminishing step size. Finally, we present a numerical example to verify the effectiveness of the algorithm. |
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| AbstractList | In this paper, we investigate a distributed constrained optimization problem subject to convex, closed, and nonidentical set constraints over unbalanced graphs, where each agent has local access to its strongly convex objective function and collaborates, minimizing the sum of these functions. To address this problem, we design a distributed projected delayed gradient algorithm by using the available delayed gradient information, which removes dependence on the current gradient information and increases iteration efficiency. Moreover, to improve communication robustness, the algorithm is only based on a row stochastic weight matrix and achieves an O(1/T) convergence rate for a non-negative and diminishing step size. Finally, we present a numerical example to verify the effectiveness of the algorithm. |
| ArticleNumber | 107466 |
| Author | Huang, Qing Fan, Yuan Cheng, Songsong |
| Author_xml | – sequence: 1 givenname: Qing orcidid: 0009-0006-0040-6926 surname: Huang fullname: Huang, Qing – sequence: 2 givenname: Yuan orcidid: 0000-0001-6716-7129 surname: Fan fullname: Fan, Yuan email: yuanf@ahu.edu.cn – sequence: 3 givenname: Songsong orcidid: 0000-0001-5566-6836 surname: Cheng fullname: Cheng, Songsong email: sscheng@ahu.edu.cn |
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| Keywords | Distributed optimization Nonidentical constraints Gradient delay Unbalanced graphs Convergence |
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| SubjectTerms | Convergence Distributed optimization Gradient delay Nonidentical constraints Unbalanced graphs |
| Title | Distributed constrained optimization over unbalanced graphs and delayed gradient |
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