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A three-step procedure for diagnosing and preventing the failure in deployed systems of Gradient-boosted trees, which under-predicts the total by 30-50x in production deployment, and by up to 496x in a public M5 reconstruction.
A forecasting benchmark reports which method won. We show that the answer is set by the evaluator's choices before any model is fitted. We benchmark 24 forecasting methods and one textbook reference, including six 2025-era time series foundation models, on a production marketplace panel of 1,887 business customers over...
Machine-learning detectors for power-system cyberattacks are themselves attack surfaces, and quantum machine learning has been proposed for them. We benchmark fidelity-kernel SVMs and variational classifiers against six tuned classical models on public power-system attack data (Mississippi State/ORNL), across white-box...
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