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Bayesian optimization with safety constraints: safe and automatic parameter tuning in robotics
Selecting the right tuning parameters for algorithms is a pravelent problem in machine learning that can significantly affect the performance of algorithms. Data-efficient optimization algorithms, such as Bayesian optimization, have been used to automate this process. During experiments on real-worl...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer US
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10485113/ https://www.ncbi.nlm.nih.gov/pubmed/37692295 http://dx.doi.org/10.1007/s10994-021-06019-1 |