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Conformal Prediction and Distribution-Free Uncertainty Quantification

Prazo para submissão: 31 October 2024

Data de Notificação: 01/04/2025

Editora: Elsevier

Revista: Pattern Recognition

Link: https://www.sciencedirect.com/special-issue/302938/conformal-prediction-and-distribution-free-uncertainty-quantification

Detalhes:

In the rapidly evolving landscape of Machine Learning and Pattern Recognition, the emergence and development of Conformal Prediction (CP) have marked a significant stride towards more reliable predictive models. CP stands out as a versatile framework capable of offering prediction regions with valid coverage guarantees under minimal assumptions. Its unique strength lies in providing probabilistically valid guarantees, which are of paramount importance for complex Pattern Recognition tasks in com

Special Issues