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Pareto optimization with small data by learning across common objective spaces
In multi-objective optimization, it becomes prohibitively difficult to cover the Pareto front (PF) as the number of points scales exponentially with the dimensionality of the objective space. The challenge is exacerbated in expensive optimization domains where evaluation data is at a premium. To ove...
Autores principales: | Tan, Chin Sheng, Gupta, Abhishek, Ong, Yew-Soon, Pratama, Mahardhika, Tan, Puay Siew, Lam, Siew Kei |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10185551/ https://www.ncbi.nlm.nih.gov/pubmed/37188695 http://dx.doi.org/10.1038/s41598-023-33414-6 |
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