Proposes Cost-Aware Adaptive Conformal Inference framework providing dual statistical guarantees on long-run violation frequency and cumulative violation cost for runtime assurance in dynamic environments.
Adaptive conformal inference for multi-step ahead time-series forecasting online.arXiv preprint arXiv:2409.14792, 2024
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BACC achieves mean absolute compliance gaps of 0.44 and 0.42 percentage points on Azure Functions traces by separating prediction, ACI-based calibration, and PI-based budget-paced control for horizontal autoscaling.
citing papers explorer
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Cost-Aware Adaptive Conformal Inference for Runtime Assurance in Dynamic Environments
Proposes Cost-Aware Adaptive Conformal Inference framework providing dual statistical guarantees on long-run violation frequency and cumulative violation cost for runtime assurance in dynamic environments.
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BACC: Budget-Aware Calibration and Control for Horizontal Autoscaling
BACC achieves mean absolute compliance gaps of 0.44 and 0.42 percentage points on Azure Functions traces by separating prediction, ACI-based calibration, and PI-based budget-paced control for horizontal autoscaling.