Tag: predictions
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SADA: Safe and Adaptive Inference with Multiple Black-Box Predictions
SADA: Safe and Adaptive Inference with Multiple Black-Box Predictions arXiv:2509.21707v1 Announce Type: new Abstract: Real-world applications often face scarce labeled data due to the high cost and time requirements of gold-standard experiments, whereas unlabeled data are typically abundant. With the growing adoption of machine learning techniques, it has become increasingly feasible to generate multiple predicted…
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Algorithms with Calibrated Machine Learning Predictions
Algorithms with Calibrated Machine Learning Predictions arXiv:2502.02861v1 Announce Type: new Abstract: The field of algorithms with predictions incorporates machine learning advice in the design of online algorithms to improve real-world performance. While this theoretical framework often assumes uniform reliability across all predictions, modern machine learning models can now provide instance-level uncertainty estimates. In this paper,…
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Predictions as Surrogates: Revisiting Surrogate Outcomes in the Age of AI
Predictions as Surrogates: Revisiting Surrogate Outcomes in the Age of AI arXiv:2501.09731v1 Announce Type: new Abstract: We establish a formal connection between the decades-old surrogate outcome model in biostatistics and economics and the emerging field of prediction-powered inference (PPI). The connection treats predictions from pre-trained models, prevalent in the age of AI, as cost-effective surrogates…