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Multitask learning and nonlinear optimal control of the COVID-19 outbreak: A geometric programming approach()
We propose a multitask learning approach to learn the parameters of a compartmental discrete-time epidemic model from various data sources and use it to design optimal control strategies of human-mobility restrictions that both curb the epidemic and minimize the economic costs associated with implem...
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| Veröffentlicht in: | Annu Rev Control |
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| Hauptverfasser: | , , |
| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
Elsevier Ltd.
2021
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| Schlagworte: | |
| Online Zugang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC8133409/ https://ncbi.nlm.nih.gov/pubmed/34040494 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.arcontrol.2021.04.014 |
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