Communication efficient quasi-Newton distributed optimization based on the Douglas-Rachford envelope
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arXiv
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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866910676333625344 |
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| author | Yi, Dingran Freris, Nikolaos M. |
| author_facet | Yi, Dingran Freris, Nikolaos M. |
| contents | We consider distributed optimization in the client-server setting. By use of Douglas-Rachford splitting to the dual of the sum problem, we design a BFGS method that requires minimal communication (sending/receiving one vector per round for each client). Our method is line search free and achieves superlinear convergence. Experiments are also used to demonstrate the merits in decreasing communication and computation costs. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_04049 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Communication efficient quasi-Newton distributed optimization based on the Douglas-Rachford envelope Yi, Dingran Freris, Nikolaos M. Optimization and Control We consider distributed optimization in the client-server setting. By use of Douglas-Rachford splitting to the dual of the sum problem, we design a BFGS method that requires minimal communication (sending/receiving one vector per round for each client). Our method is line search free and achieves superlinear convergence. Experiments are also used to demonstrate the merits in decreasing communication and computation costs. |
| title | Communication efficient quasi-Newton distributed optimization based on the Douglas-Rachford envelope |
| topic | Optimization and Control |
| url | https://arxiv.org/abs/2409.04049 |