CORDIS Project
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This project focuses on understanding and quantifying the uncertainty in predictions made by large-scale machine learning systems. It aims to develop new statistical methods to ensure the reliability of these systems, particularly in decision-making applications.
Assessing the uncertainty of predictions of modern large-scale machine learning systems is crucial for understanding their limitations and the quality of solutions they provide, especially so when these systems are used for making decisions in the real world.
Motivated by this need, this project addresses a variety of questions of uncertainty quantification and develops new methods for deriving statistical guarantees on the accuracy of outputs of ML systems.
Our methodology is inspired by an eme…
UNIVERSIDAD POMPEU FABRA
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