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GAS: Generating Fast and Accurate Surrogate Models for Autonomous Vehicle Systems
GAS's approach also allows for reuse of the perception model when vehicle control and dynamics characteristics are altered during vehicle development, saving significant time.
PAC Learning-Based Verification and Model Synthesis
Our learning procedure is therefore based on the framework of probably approximately correct (PAC) learning, which uses sampling instead and provides correctness guarantees expressed using the terms error probability and confidence.
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