ModelGuard: Runtime Validation of Lipschitz-continuous Models
نویسندگان
چکیده
This paper presents ModelGuard, a sampling-based approach to runtime model validation for Lipschitz-continuous models. Although techniques exist the of many classes models, majority these methods cannot be applied whole which includes neural network Additionally, existing generally consider only white-box By taking approach, we can address black-box represented by an input-output relationship and Lipschitz constant. We show that randomly sampling from parameter space evaluating model, it is possible guarantee correctness traces labeled consistent provide confidence on inconsistent. evaluate applicability scalability ModelGuard in three case studies, including physical platform.
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ژورنال
عنوان ژورنال: IFAC-PapersOnLine
سال: 2021
ISSN: ['2405-8963', '2405-8971']
DOI: https://doi.org/10.1016/j.ifacol.2021.08.471