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• W3106675131 abstract "Despite the existence of formal guarantees for learning-based control approaches, the relationship between data and control performance is still poorly understood. In this paper, we present a measure to quantify the value of data within the context of a predefined control task. Our approach is applicable to a wide variety of unknown nonlinear systems that are to be controlled by a generic learning-based control law. We model the unknown component of the system using Gaussian processes, which in turn allows us to directly assess the impact of model uncertainty on control. Results obtained in numerical simulations indicate the efficacy of the proposed measure." @default.
• W3106675131 created "2020-12-07" @default.
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• W3106675131 date "2020-11-20" @default.
• W3106675131 modified "2023-09-27" @default.
• W3106675131 title "The Value of Data in Learning-Based Control for Training Subset Selection." @default.
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• W3106675131 hasPublicationYear "2020" @default.
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