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Found 2 papers, 1 papers with code
Tuning Particle Accelerators with Safety Constraints using Bayesian Optimization
Tuning machine parameters of particle accelerators is a repetitive and time-consuming task that is challenging to automate.
Adaptive and Safe Bayesian Optimization in High Dimensions via One-Dimensional Subspaces
In order to scale the method and keep its benefits, we propose an algorithm (LineBO) that restricts the problem to a sequence of iteratively chosen one-dimensional sub-problems that can be solved efficiently.
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