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Prior-mean-assisted Bayesian optimization application on FRIB Front-End tunning
November 11, 2022 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
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Authors
Kilean Hwang, Tomofumi Maruta, Alexander Plastun, Kei Fukushima, Tong Zhang, Qiang Zhao, Peter Ostroumov, Yue Hao
arXiv ID
2211.06400
Category
physics.acc-ph
Cross-listed
cs.LG
Citations
5
Venue
arXiv.org
Last Checked
3 months ago
Abstract
Bayesian optimization~(BO) is often used for accelerator tuning due to its high sample efficiency. However, the computational scalability of training over large data-set can be problematic and the adoption of historical data in a computationally efficient way is not trivial. Here, we exploit a neural network model trained over historical data as a prior mean of BO for FRIB Front-End tuning.
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