BARGAIN uses betting-based anytime-valid tests and adaptive, target-aware sampling to set model-cascade thresholds, delivering non-asymptotic quality guarantees and up to 86% greater cost savings than SUPG.
2017.Probability and computing: Random- ization and probabilistic techniques in algorithms and data analysis
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Cut Costs, Not Accuracy: LLM-Powered Data Processing with Guarantees
BARGAIN uses betting-based anytime-valid tests and adaptive, target-aware sampling to set model-cascade thresholds, delivering non-asymptotic quality guarantees and up to 86% greater cost savings than SUPG.