Applies conformalized quantile regression with equalized coverage to predict motion control performance in automated vehicles under nominal, degraded, and failed actuator conditions.
In:Studies in Fuzziness and Soft Computing, vol 207
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A graphical heuristic constructs an information graph via approximate nearest neighbors and applies clustering to reduce or partition training data, achieving faster training than LIBSVM's shrinking heuristic with comparable or better prediction accuracy.
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Equalized Coverage in Motion Control Performance Prediction for Self-Adaptive Road Vehicles
Applies conformalized quantile regression with equalized coverage to predict motion control performance in automated vehicles under nominal, degraded, and failed actuator conditions.
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A graphical heuristic for reduction and partitioning of large datasets for scalable supervised training
A graphical heuristic constructs an information graph via approximate nearest neighbors and applies clustering to reduce or partition training data, achieving faster training than LIBSVM's shrinking heuristic with comparable or better prediction accuracy.