PPI++: Efficient Prediction-Powered Inference

• URL: http://arxiv.org/abs/2311.01453v2
• Date: Tue, 26 Mar 2024 01:44:52 GMT
• Title: PPI++: Efficient Prediction-Powered Inference
• Authors: Anastasios N. Angelopoulos, John C. Duchi, Tijana Zrnic,
• Abstract summary: We present PPI++: a methodology for estimation and inference based on a small labeled dataset and a typically much larger dataset of machine-learning predictions. The methods automatically adapt to the quality of available predictions, yielding easy-to-compute confidence sets. PPI++ builds on prediction-powered inference (PPI), which targets the same problem setting, improving its computational and statistical efficiency.
• Score: 31.403415618169433
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We present PPI++: a computationally lightweight methodology for estimation and inference based on a small labeled dataset and a typically much larger dataset of machine-learning predictions. The methods automatically adapt to the quality of available predictions, yielding easy-to-compute confidence sets -- for parameters of any dimensionality -- that always improve on classical intervals using only the labeled data. PPI++ builds on prediction-powered inference (PPI), which targets the same problem setting, improving its computational and statistical efficiency. Real and synthetic experiments demonstrate the benefits of the proposed adaptations.

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