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Stagewise Safe Bayesian Optimization with Gaussian Processes

Sui, Yanan and Zhuang, Vincent and Burdick, Joel W. and Yue, Yisong (2018) Stagewise Safe Bayesian Optimization with Gaussian Processes. Proceedings of Machine Learning Research, 80 . pp. 4781-4789. ISSN 1938-7228.

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Enforcing safety is a key aspect of many problems pertaining to sequential decision making under uncertainty, which require the decisions made at every step to be both informative of the optimal decision and also safe. For example, we value both efficacy and comfort in medical therapy, and efficiency and safety in robotic control. We consider this problem of optimizing an unknown utility function with absolute feedback or preference feedback subject to unknown safety constraints. We develop an efficient safe Bayesian optimization algorithm, StageOpt, that separates safe region expansion and utility function maximization into two distinct stages. Compared to existing approaches which interleave between expansion and optimization, we show that StageOpt is more efficient and naturally applicable to a broader class of problems. We provide theoretical guarantees for both the satisfaction of safety constraints as well as convergence to the optimal utility value. We evaluate StageOpt on both a variety of synthetic experiments, as well as in clinical practice. We demonstrate that StageOpt is more effective than existing safe optimization approaches, and is able to safely and effectively optimize spinal cord stimulation therapy in our clinical experiments.

Item Type:Article
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Yue, Yisong0000-0001-9127-1989
Additional Information:© 2018 by the author(s). This research was also supported in part by NSF Awards #1564330 & #1637598, JPL PDF IAMS100224, a Bloomberg Data Science Research Grant, and a gift from Northrop Grumman.
Funding AgencyGrant Number
JPL President and Director's FundIAMS100224
Bloomberg Data ScienceUNSPECIFIED
Northrop GrummanUNSPECIFIED
Record Number:CaltechAUTHORS:20190205-102511954
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Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:92663
Deposited By: Tony Diaz
Deposited On:05 Feb 2019 18:59
Last Modified:03 Oct 2019 20:46

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